Patent Publication Number: US-10788887-B2

Title: Image generation program, image generation device, and image generation method

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is based upon and claims the benefit of priority of the prior Japanese Patent Application No. 2017-233534, filed on Dec. 5, 2017, the entire contents of which are incorporated herein by reference. 
     FIELD 
     The embodiments discussed herein are related to an image generation program, an image generation device, and an image generation method. 
     BACKGROUND 
     There has been known a technology that achieves communications among users at remote locations by way of an avatar in a virtual space or a robot in a real space (avatar in a broad sense), the robot simulating a user&#39;s actions. Related techniques are disclosed in, for example, Japanese Laid-open Patent Publication Nos. 2009-77380 and 2006-262010. 
     However, unlike communications directly performed by users in a real space, communications achieved in communication service described above have low immediacy. There is thus a problem that a reactive behavior (for example, a behavior with high immediacy such as a partner (user) looking at a speaker in response to the speaker starting to speak) may not be presented to a communication partner. 
     SUMMARY 
     According to an aspect of the embodiments, an image generation method, for displaying avatars, is disclosed. The method includes: identifying tendency in a predetermined temporal interval of a social behavior performed by a second user to a first user if the first user performs the social behavior to the second user, of the users performing communications by way of avatars; and controlling such that the social behavior selected based on the identified tendency is presented to the first user by way of the avatar of the second user, if the first user performs the social behavior to the second user. 
     The object and advantages of the invention will be realized and attained by means of the elements and combinations particularly pointed out in the claims. 
     It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are not restrictive of the invention. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a diagram illustrating an example of an overall configuration of an image generation system; 
         FIG. 2  is a diagram illustrating an example of an image in a virtual space; 
         FIG. 3  is a diagram illustrating an example of an expression method of an avatar image; 
         FIG. 4  is a diagram illustrating basic information on a social behavior; 
         FIG. 5  is a diagram illustrating an example of a hardware configuration of an image generation device; 
         FIG. 6  is a diagram illustrating an example of the hardware configuration of an HMD mounted with an information processor; 
         FIG. 7  is a diagram illustrating an overview of presentation control processing of a reactive processing unit of the image generation device; 
         FIG. 8  is a first diagram illustrating a functional configuration of the reactive processing unit of the image generation device; 
         FIGS. 9A to 9C  are diagrams illustrating examples of respective tables stored in a sensor data DB; 
         FIG. 10  is a diagram illustrating an example of a log table relating to avatar display information stored in a log DB; 
         FIG. 11  is a diagram illustrating an example of a monitoring target data log definition data table stored in a definition data DB; 
         FIG. 12  is a diagram illustrating an example of a social behavior judgment API definition data table stored in the definition data DB; 
         FIG. 13  is a diagram illustrating an example of a social behavior approach and avoidance tendency definition data table stored in the definition data DB; 
         FIG. 14  is a diagram illustrating an example of a control definition data table on whether a reactive social behavior for a dialogue strategy is permitted, stored in the definition data DB; 
         FIG. 15  is a first flowchart illustrating details of the presentation control processing of the reactive processing unit; 
         FIGS. 16A to 16D  are diagrams illustrating an example of a behavior log update recording table recorded in an evaluation information DB; 
         FIG. 17  is a diagram illustrating an example of a social behavior log recording table recorded in the evaluation information DB; 
         FIGS. 18A and 18B  are diagrams illustrating an example of a social behavior value calculation recording table recorded in the evaluation information DB; 
         FIG. 19  is a diagram illustrating an example of a dialogue strategy determination recording table recorded in the evaluation information DB; 
         FIG. 20  is a second diagram illustrating the functional configuration of the reactive processing unit of the image generation device; 
         FIG. 21  is a diagram illustrating an example of a temporal interval social behavior action tendency amount threshold definition data table stored in the definition data DB; 
         FIG. 22  is a first flowchart illustrating details of dialogue strategy determination processing of the reactive processing unit; 
         FIG. 23  is a diagram illustrating a temporal interval social behavior action tendency amount recording table recorded in the definition data DB; 
         FIG. 24  is a diagram illustrating an example of a temporal interval social behavior action tendency recording table recorded in the evaluation information DB; 
         FIG. 25  is a diagram illustrating an example of a cooperative action possibility judgment recording table recorded in the evaluation information DB; 
         FIG. 26  is a diagram illustrating an example of a social behavior acceptability judgment recording table recorded in the evaluation information DB; 
         FIG. 27  is a diagram illustrating an example of a recording table of dialogue strategy determination corresponding to social behavior acceptability, recorded in the evaluation information DB; 
         FIG. 28  is a third diagram illustrating the functional configuration of the reactive processing unit of the image generation device; 
         FIG. 29  is a diagram illustrating an example of a dialogue strategy definition data table by relationship level, stored in the definition data DB; 
         FIG. 30  is a second flowchart illustrating details of the dialogue strategy determination processing of the reactive processing unit; 
         FIG. 31  is a diagram illustrating an example of a speech value calculation recording table recorded in the evaluation information DB; 
         FIG. 32  is a flowchart illustrating details of relationship level processing; 
         FIG. 33  is a diagram illustrating an example of a recording table of information disclosure amount to dialogue partner recorded in the evaluation information DB; 
         FIG. 34  is a diagram illustrating an example of a judgment recording table of relationship level considered appropriate to dialogue partner, recorded in the evaluation information DB; 
         FIG. 35  is a diagram illustrating an example of a relationship progress degree recording table, recorded in the evaluation information DB; 
         FIG. 36  is a flowchart illustrating details of relatedness level processing; 
         FIG. 37  is a diagram illustrating an example of a recording table of information disclosed amount from dialogue partner, recorded the evaluation information DB; 
         FIG. 38  is a diagram illustrating an example of a relatedness level estimation recording table considering dialogue partner appropriate based on information disclosed amount from dialogue partner, recorded in the evaluation information DB; 
         FIG. 39  is a flowchart illustrating details of relationship adjustment control processing; 
         FIG. 40  is a flowchart illustrating details of the dialogue strategy determination processing based on relationship adjustment control; 
         FIG. 41  is a diagram illustrating an example of a recording table of dialogue strategy determination corresponding to relationship level, recorded in the evaluation information DB; 
         FIG. 42  is a fourth diagram illustrating the functional configuration of the reactive processing unit of the image generation device; 
         FIG. 43  is a diagram illustrating an example of a reactive social behavior definition data table per dialogue strategy, stored in the definition data DB; 
         FIG. 44  is a diagram illustrating an example of a social behavior group definition data table stored in the definition data DB; 
         FIG. 45  is a diagram illustrating an approach and avoidance tendency evaluation value definition data table of social behavior and social behavior group, stored in the definition data DB; 
         FIG. 46  is a second flowchart illustrating details of the presentation control processing of the reactive processing unit; 
         FIG. 47  is a flowchart illustrating details of an execution stack registration processing; 
         FIG. 48  is a first diagram illustrating an example of a recording table of social behavior in execution stack, recorded in the evaluation information DB; 
         FIG. 49  is a flowchart illustrating details of synthesis processing; 
         FIGS. 50A and 50B  are second diagrams illustrating an example of the recording table of social behavior in execution stack, recorded in the evaluation information DB; 
         FIG. 51  is a third diagram illustrating an example of the recording table of social behavior in execution stack, recorded in the evaluation information DB; 
         FIG. 52  is a fourth diagram illustrating an example of the recording table of social behavior in execution stack, recorded in the evaluation information DB; 
         FIG. 53  is a fifth diagram illustrating an example of the recording table of social behavior in execution stack, recorded in the evaluation information DB; 
         FIG. 54  is a sixth diagram illustrating an example of the recording table of social behavior in execution stack, recorded in the evaluation information DB; 
         FIG. 55  is a seventh diagram illustrating an example of the recording table of social behavior in execution stack, recorded in the evaluation information DB; 
         FIG. 56  is a flowchart illustrating details of the presentation control processing based on the execution stack; and 
         FIG. 57  is a diagram illustrating an example of a social behavior control log table recorded in the evaluation information DB. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     In the following, respective embodiments are described with reference to the attached drawings. Note that in this specification and the drawings, an overlapping description is omitted by assignment of identical numerals to components having substantially identical function and configuration. 
     First Embodiment 
     &lt;Overall Configuration of Image Generation System&gt; 
     First, an image generation system is described.  FIG. 1  is a diagram illustrating an example of an overall configuration of an image generation system. As illustrated in  FIG. 1 , the image generation system  100  includes an image generation device  110  where server software is located, and client-side systems  120 ,  130  respectively including an information processor  121 ,  131  where client application software is located. The image generation device  110  and the client-side systems  120 ,  130  are connected by way of a network  160  such as the Internet or a Local Area Network (LAN) or the like. 
     In the image generation system  100 , the image generation device  110  and the client-side systems  120 ,  130  divide and execute overall processing. With this, the image generation system  100  provides a communication service that achieves communications between users by way of an avatar (image in a state associated with a user). 
     A user  140  (user ID=“userA”) and a user  150  (user ID=“userB”) utilize the communication service provided by the image generation system  100  at separate locations. By using the communication service, the users  140  and  150  may perform communications by way of the avatar in a same virtual space. 
     The image generation device  110  is a server device that collects sensor data obtained by sensing actions of the users  140  and  150  and performs various types of processing. 
     An image generation program is installed as the server software in the image generation device  110 . The image generation program being executed, the image generation device  110  includes a basic function unit  1101  and a reactive processing unit  115 . 
     The basic function unit  1101  includes an information collection processing management section  111 , an information display processing section  112 , a registration data management section  113 , and a display history management section  114 , and performs basic functions for providing the communication service. 
     The information collection processing management section  111  collects and stores, in a sensor data database (hereinafter referred to as Database (DB))  116   b , the sensor data obtained as a result of the sensing of the actions of the users  140  and  150 . 
     The information display processing section  112  generates an image of the avatar in the virtual space based on the sensor data stored in the sensor data DB  116   b . The information display processing section  112  generates the avatar image using an avatar skeleton model stored in a content DB  116   a.    
     The avatar skeleton model is a human-like image, and is an image expressing an action of each part of the user, using a plurality of the avatar skeleton models. Note that an avatar skeleton is an object serving as a base point to move avatar&#39;s head or limbs. A plurality of the avatar skeletons are included in one avatar skeleton model. 
     The information display processing section  112  calculates, for each of the avatar skeletons, positional coordinates and a rotation angle in the virtual space based on the sensor data, and reflects the calculated positional coordinates and rotation angle in the avatar skeleton model, thereby generating the avatar image. 
     The information display processing section  112  also generates virtual space information by incorporating the avatar image into an image (background image) of the virtual space stored in the content DB  116   a  and transmits the virtual space information to the client-side systems  120 ,  130 . 
     Note that the information display processing section  112  changes the avatar image to be incorporated into the image of the virtual space based on an instruction from the reactive processing unit  115 . For example, if the reactive processing unit  115  issues the instruction to display the avatar image generated by the reactive processing unit  115 , the information display processing section  112  generates the virtual space information by incorporating the avatar image generated by the reactive processing unit  115 . 
     The registration data management section  113  registers various types of information in the content DB  116   a , the definition data DB  118 , or the like, the various types of information being used until the information collection processing management section  111  collects the sensor data and the information display processing section  112  generates and transmits the virtual space information. 
     The display history management section  114  records, in a “log table related to display information” stored in the log DB  117 , the data used for generation of the avatar image included in the virtual space information transmitted by the information display processing section  112 . Note that the data used for generation of the avatar image is specifically the data on the positional coordinates and the rotation angle of the respective avatar skeletons. 
     The reactive processing unit  115  generates an image of the avatar depicting a reactive behavior of a second user, in a scene where the second user desirably performs the reactive behavior to a first user. The reactive processing unit  115  also instructs the information display processing section  112  to display the generated avatar image. 
     This is because in the scene where it is desirable to perform the reactive behavior, it is not possible to present the reactive behavior to the first user even if the avatar image is generated based on the sensor data that senses an actual action of the second user. 
     Thus, the reactive processing unit  115  generates the avatar image based on the reactive behavior that would be performed by the second user to the first user. This enables the reactive processing unit  115  to achieve presentation control processing that presents to the first user the second user&#39;s reactive behavior, without waiting for the sensor data that senses the actual action by the second user. 
     Note that in the following, a description is given on the assumption that the first user is the user  140  (user ID=“userA”) and the second user is the user  150  (user ID=“userB”). In addition, in the following, a partner (user) to whom the reactive behavior is performed is referred to as a “dialogue partner”. 
     Subsequently, the client-side system is described. As illustrated in  FIG. 1 , in the image generation system  100 , the client-side system  120  and the client-side system  130  have a similar configuration. Namely, the elements  1201 ,  121 - 126  may have similar or same functionalities as the elements  1301 ,  131 - 136 , respectively. Thus, the client-side system  120  is described here. 
     The client-side system  120  includes an information processor  121 , an information presentation device  123 , and information collectors  124  to  126 . 
     In the information processor  121 , an information processing program is installed as client application software. The information processing program being executed, the information processor  121  serves as the information processing section  122 . The information processing section  122  transmits to the image generation device  110  the sensor data outputted from the information collectors  124  to  126 , and receives and outputs to the information presentation device  123  the virtual space information transmitted from the image generation device  110 . 
     Note that although in the first embodiment, the information processor  121  is described as an information processor mounted in a head-mounted display (HMD)  1201 , the information processor  121  may not be mounted in the HMD. For example, the information processor  121  may be mounted in an environmentally embedded type terminal surrounding the user  140 . Alternatively, the information processor  121  may be mounted in a wearable mobile terminal such as contact lenses and glasses or a stationary server device or the like. 
     The information presentation device  123  displays to the user  140  the virtual space information transmitted from the image generation device  110 . Note that in the first embodiment, the information presentation device  123  is implemented by a display device of the HMD  1201 . 
     Each of the information collectors  124  to  126  senses a non-verbal action of the user  140  in a real space and outputs the sensor data. 
     In the first embodiment, the information collector  124  is a head posture sensor and mounted in the HMD  1201 . A head posture sensor  124  senses “head position/orientation” included in the non-verbal action of the user  140  in the real space and outputs head posture data. 
     In addition, in the first embodiment, the information collector  125  is a depth sensor. The depth sensor  125  is placed in front of the user  140 , and outputs depth data and two-dimensional distance image or the like by sensing a three-dimensional distance from the location of placement to the user  140 , the depth data and the two-dimensional distance image or the like varying depending on the non-verbal action of the user  140  in the real space. The depth data is data representing a depth (deepness) (3 cm or the like, for example). In addition, the distance image refers to an image obtained by plotting the depth data obtained from the depth sensor  125  on an XY plane. In each pixel on the distance image is stored a value of a distance to an object on each of XY coordinate positions obtained from the depth sensor  125  (nearest object when viewed from the depth sensor  125 ). Note that the data obtained from the depth sensor  125  (including a color image or the like, in addition to the depth data and the distance image) is collectively referred to as depth sensor data. 
     In addition, in the first embodiment, the information collector  126  is a muscle potential sensor (a.k.a. a Myoelectricity (EMG) sensor). The muscle potential sensor  126  senses a “facial expression change” included in the non-verbal action of the user  140  in the real space and outputs muscle potential data (or EMG data). 
     Note that in the following, although the description is given on the assumption that one user is assigned on one device (information processor) on which the client application software is located, a plurality of users may be assigned on the one device. 
     In addition, in the following, although the description is given on the assumption that each of the server software and the client application software is located on one device (image generation device, information processor), more than one software may be located on the one device. 
     Alternatively, the server software and the client application software may be located on one device. For example, an image processing program and the information processing program may be installed in each of the information processors  121 ,  131 . 
     Alternatively, for both the server software and the client application software, functions implemented in each of the software may be distributed and located in a plurality of devices. 
     In addition, in the following, the client application software identifies the user  140 , and transforms the virtual space information transmitted from the image generation device  110  into the virtual space information corresponding to the identified user  140  and displays the virtual space information. In addition, in the following, the description is given on the assumption that the sensor data obtained as a result of the sensing of the non-verbal action of the user  140  is associated with the user  140  and then transmitted to the image generation device  110 . 
     Note that the information processor  121  in which the client application software is located is access controlled by the client application software or the server software. That is to say, in the following, the client application software is started only when identity confirmation (user authentication) is performed in advance at the information processor  121  in which the client application software is located. 
     In addition, in the following, the client application software confirms specifications of the information presentation device  123 , transforms the virtual space information transmitted from the image generation device  110  into virtual space information corresponding to the confirmed specifications, and displays the virtual space information. 
     In addition, in the following, the client application software checks the information processor  121 , associates the sensor data obtained as a result of the sensing of the non-verbal action of the user  140  with the information processor  121 , and transmits the sensor data to the image generation device  110 . 
     In addition, in the following, although the description is given on the assumption that the user  140  has one kind of an identifier for identifying the user  140 , the user  140  may have identifiers that differ for each service in a case where the image generation system  100  provides a plurality of services. In that case, however, the image generation system  100  manages association of the plurality of identifiers that the user  140  has. 
     In addition, in the following, although the description is given on the assumption that the head posture sensor, the depth sensor, and the muscle potential sensor sense the non-verbal action of the user  140  as the information collectors  124  to  126 , any other sensor may sense the non-verbal action of the user  140 . The other sensor includes, for example, an image capturing device, a photo image (color image) capturing device, a voice capturing device (microphone or the like), a biological sensor, a brain wave sensor, or the like. Here, “voice” may include not only a human voice, but also any kind of audio sound. 
     Note that in a contactless sensor, no data of the user  140  may exist in the sensor data, as such a case where the user  140  is not seen in the photo image taking the user  140 . In addition, for example, there is also a case where more than one user is shown in the photo image shooting the user  140 , and it is not distinguishable which user is sensed. In the present embodiment, a measure is separately taken on such an event, and the sensor data is correctly associated with the user  140  in the image generation device  110 . 
     In addition, in the following, although the description is given on the assumption that the sensor data itself sensed by the information collectors  124  to  126  is transmitted to the image generation device  110 , intermediate information derivable from the sensed sensor data may be transmitted. For example, if facial image data of the user  140  is sensed, information representing big and small changes in a smile derived by focusing on facial parts of the user  140  may be transmitted to the image generation device  110 . Alternatively, information representing a posture change derived by focusing on size of a face of the user  140  may be transmitted to the image generation device  110 . 
     In addition, in the following, a time stamp is added to the sensor data transmitted from the information processors  121 ,  131 . In addition, for the time stamp to be added at this time, the time is set between the client-side system  120  and the client-side system  130 . 
     Furthermore, in the following, although the description is given based on a display unit as the information presentation device  123 , the HMD  1201  may have another information presentation device. The information presentation device other than the display unit includes a voice output device (speaker or the like), for example. 
     &lt;Image in Virtual Space&gt; 
     In the following, description is given of the virtual space image including the avatar image of the user  140 ,  150 .  FIG. 2  is a diagram illustrating an example of the image in the virtual space. 
     As illustrated in  FIG. 2 , in the real space, the user  140  utilizing the communication service puts on the HMD  1201  (HMD mounted with the head posture sensor  124  and the display unit  123 ) and the muscle potential sensor  126  and sits on a chair  200 , for example. In addition, the depth sensor  125  is placed in front of the user  140  and senses the user  140 . 
     The head posture data, the depth sensor data, and the muscle potential data that the head posture sensor  124 , the depth sensor  125 , and the muscle potential sensor  126  obtain by sensing are transmitted to the image generation device  110 , and the avatar image of the user  140  is generated in the image generation device  110 . Similar processing is also performed on the user  150  and the avatar image of the user  150  is generated in the image generation device  110 . 
     Furthermore, the avatar image generated in the image generation device  110  is incorporated into the virtual space image and transmitted as the virtual space information to the information processors  121  and  131 , respectively, illustrated in  FIG. 1 . 
     An image  210  illustrated in  FIG. 2  is an example of the virtual space image included in the virtual space information transmitted to the information processor  121 . The image  210  includes the avatar image  220  of the user  140  and the avatar image  230  of the user  150 . As illustrated in  FIG. 2 , the image  210  is displayed as if the user  140  is looking at the image  220  of his or her own avatar from behind. If the user  140  performs the non-verbal action in this state, the avatar image  220  in the image  210  also changes. According to the image  210 , from behind of the avatar image  220 , the user  140  may confirm the avatar image  220  changing in the virtual space in accordance with his or her own non-verbal action. Note that a display aspect of the avatar image  220  in the image  210  is not limited thereto, and the avatar image  220  may be displayed as if the user  140  sees from a position of his or her own eyes, like a case where the user  140  looks in the real space. In this case, the user  140  visually recognizes a part (arm or leg, or the like) of the avatar image  220 . 
     &lt;Manner of Expression of Avatar Image&gt; 
     In the following, description is given of a manner of expression of the avatar image in the virtual space. The avatar image in the virtual space may be expressed, using a different manner of expression by the part, in order to reflect the user&#39;s non-verbal action in the real space. In the following, however, the description is given on the assumption that any part is expressed by means of the avatar skeleton level. 
     As described above, the plurality of the avatar skeletons may be included in one avatar skeleton model. For example, a head of the avatar skeleton model includes the avatar skeleton of the head. The positional coordinates and the rotation angle of the avatar skeleton of the head are calculated based on the head posture data. In addition, the limbs of the avatar skeleton model other than the head include the avatar skeletons of the limbs other than the head. These positional coordinates and rotation angle of the avatar skeletons are calculated based on the depth sensor data. 
     Here, by way of example, description is given of the manner of expression for expressing an image of an upper body of the avatar using the avatar skeleton model.  FIG. 3  is a diagram illustrating an example of the manner of expression of an avatar image, and expresses, as the avatar image, the user&#39;s action to bend his or her upper body forward or backward, the user&#39;s action to change orientation of his or her upper body so as to look from side to side, and the action to swing the entire upper body to a left or right lateral face. In the case of the manner of expression using the avatar skeleton model, these actions may be expressed as a change of the rotation angle of the avatar skeleton (“Bone_Chest”) relative to three axis directions with a position of the avatar&#39;s waist as an origin. 
     Note that in  FIG. 3 , an X-axis, a Y-axis, and a Z-axis of a coordinate system uniquely defined in the virtual space is respectively made a right-left direction, an up-down direction, and a forward-backward direction of the avatar. 
     An image  301  represents the avatar image when the avatar skeleton rotates +α [degrees] relative to the X-axis, and an image  302  represents the avatar image when the avatar skeleton rotates −α [degrees] relative to the X-axis. In addition, an image  311  represents the avatar image when the avatar skeleton rotates +α [degrees] relative to the Y-axis, and an image  312  represents the avatar image when the avatar skeleton rotates −α [degrees] relative to the Y-axis. 
     Furthermore, an image  321  represents the avatar image when the avatar skeleton rotates +α[degrees] relative to the Z-axis, and an image  322  represents the avatar image when the avatar skeleton rotates −α[degrees] relative to the Z-axis. 
     &lt;Basic Information on Social Behavior&gt; 
     In the following, a social behavior and basic information used to judge the social behavior are described. The social behavior (Social Behavior) refers to a non-verbal action to be done on a social entity, among predetermined human non-verbal actions in the real space. 
     For example, if non-verbal action of a predetermined person is the non-verbal action to go forward, it may be said that the non-verbal action of the predetermined person is the social behavior of approaching to other person (social behavior indicating approach tendency) when the other person is present at a destination to which the predetermined person goes. To the contrary, if the predetermined person performs the non-verbal action to go forward when the other person is nearby and as a result, the other person moves away, it may be said that the non-verbal action of the predetermined person is the social behavior of letting the other person move away (social behavior indicating avoidance tendency). 
     Similarly, for example, if the non-verbal action of a predetermined person is the non-verbal action to turn a position and orientation of his or her head to the right, and when the other person is on the right side, it may be said that the non-verbal action of the predetermined person is the social behavior of turning his or her face to the other person. That is, it may be said that the non-verbal action of the predetermined person is the social behavior indicating the approach tendency. To the contrary, if the predetermined person performs the non-verbal action to go forward while the other person is nearby and as a result, he or she moves away from the other person, it may be said that the non-verbal action of the predetermined person is the social behavior of moving away from the other person (social behavior indicating the avoidance tendency). 
     Thus, if the social behavior is judged in the virtual space, it is desirable to calculate the basic information such as a physical distance or a rotation angle between the avatar of the predetermined person and the avatar of the other person. 
       FIG. 4  is a diagram illustrating the basic information on the social behavior. In the image  210  illustrated in  FIG. 4 , suppose that the positional coordinates in the virtual space of the image  220  of the avatar of the user  140  (illustrated in  FIG. 1 ) (avatar ID=“AV 1 ”) are (0, 0, 0). In addition, suppose that the positional coordinates in the virtual space of the image  230  of the avatar of the user  150  (illustrated in  FIG. 1 ) (avatar ID=“AV 2 ”) are (10, 0, 17.32). In this case, as the basic information, the physical distance between the image  220  of the avatar of the user  140  and the image  230  of the avatar of the user  150  may be calculated to be “20 (=0.2 [m])”. 
     In addition, in  FIG. 4 , suppose that the rotation angle in the virtual space of the image  220  of the avatar of the user  140  is (0, 0, 0) and the rotation angle in the virtual space of the image  230  of the avatar of the user  150  is (0, −90, 0). In this case, as the basic information, the rotation angle on an XZ plane from a front-back direction of the image  230  of the avatar of the user  150  to the image  220  of the avatar of the user  140  may be calculated to be “−90 [degrees]”. In addition, as the basic information, the rotation angle on the XZ plane from the front-back direction of the image  220  of the avatar of the user  140  to the image  230  of the avatar of the user  150  may be calculated to be “+90 [degrees]”. 
     Note that in the example of  FIG. 4 , an image  410  of the object is also placed in the virtual space, in addition to the image  220  of the avatar of the user  140  and the image  230  of the avatar of the user  150 . The positional coordinates in the virtual space of the image  410  of the object is (−6, 21, 17), and the rotation angle in the virtual space is (90, 140, 0). Therefore, the basic information may also be calculated for the image  410  of the object. 
     &lt;Hardware Configuration of Image Generation Device&gt; 
     In the following, description is given of a hardware configuration of the image generation device  110  included in the image generation system  100  (illustrated in  FIG. 1 ).  FIG. 5  is a diagram illustrating an example of the hardware configuration of the image generation device  110 . As illustrated in  FIG. 5 , the image generation device  110  includes a central processing unit (CPU)  501 , a read only memory (ROM)  502 , and a random access memory (RAM)  503 . The CPU  501 , the ROM  502 , and the RAM  503  form a computer. In addition, the image generation device  110  includes an auxiliary storage unit  504 , a communication unit  505 , a display unit  506 , an operation unit  507 , and a drive unit  508 . Note that each component of the image generation device  110  is mutually connected via a bus  509 . 
     The CPU  501  executes various programs (for example, an image generation program as server software) installed in the auxiliary storage unit  504 . The ROM  502  is a non-volatile memory. The ROM  502  is a main storage unit that stores various programs, data, or the like which are desirable for the CPU  501  to execute the various programs stored in the auxiliary storage unit  504 . Specifically, the ROM  502  stores a boot program or the like such as a basic input/output system (BIOS) or an extensible firmware interface (EFI). 
     The RAM  503  is a volatile memory such as a dynamic random access memory (DRAM) or a static random access memory (SRAM), and acts as the main storage unit. The RAM  503  provides a working area to be expanded when the CPU  501  executes the various programs stored in the auxiliary storage unit  504 . 
     The auxiliary storage unit  504  stores various programs installed in the image generation device  110  or information (various contents, various definition information, or the like) to be used when the various programs are executed. The auxiliary storage unit  504  also stores information (sensor data, log table, or the like) to be acquired through execution of the various programs. Note that the foregoing content DB  116   a , sensor data DB  116   b , log DB  117 , definition data DB  118 , and an evaluation information DB  119  may be implemented in the auxiliary storage unit  504 . 
     The communication unit  505  is a device for communicating with the information processors  121 ,  131  of the client-side systems  120 ,  130  (each of which is illustrated in  FIG. 1 ) connected to the image generation device  110 . The display unit  506  is a device that displays a processing result or a processing state of the image generation device  110 . The operation unit  507  is a device for inputting various instructions to the image generation device  110 . 
     The drive unit  508  is a device for setting a recording medium  510 . The recording medium  510  used herein includes a medium that optically, electrically, or magnetically stores information, such as a CD-ROM, a flexible disk, a magneto-optic disk. The recording medium  510  may also include a semiconductor memory or the like that electrically stores information, such as the ROM, a flash memory, or the like. 
     Note that the various programs to be installed in the auxiliary storage unit  504  are installed by, for example, the distributed recording medium  510  being set in the drive unit  508 , and the various programs recorded in the recording medium  510  being read by the drive unit  508 . Alternatively, the various programs to be installed in the auxiliary storage unit  504  may be installed through downloading from the network  160  (illustrated in  FIG. 1 ) by way of the communication unit  505 . 
     &lt;Hardware Configuration of HMD Mounted with Information Processor&gt; 
     In the following, description is given of a hardware configuration of the HMD  1201  mounted with the information processor  121 .  FIG. 6  is a diagram illustrating an example of the hardware configuration of the HMD mounted with which the information processor. As illustrated in  FIG. 6 , the information processor  121  mounted in the HMD includes a CPU  601 , a ROM  602 , and a RAM  603 . The information processor  121  mounted in the HMD also includes an auxiliary storage unit  604  and a communication unit  605 . The HMD further includes an operation unit  606 , a display unit  123 , the head posture sensor  124 , and an interface (I/F) unit  607 , and the respective components are mutually connected via a bus  608 . Note that although the voice output device (speaker, or the like) as other sensor or the voice capturing device (microphone, or the like) as other information presentation device is placed in the HMD, the voice output device and the voice capturing device are omitted here. 
     The CPU  601  executes the various programs (for example, the information processing program as client application software) installed in the auxiliary storage unit  604 . The ROM  602  is a non-volatile memory. The ROM  602  is the main storage unit that stores various programs, data, or the like which are desirable for the CPU  601  to execute the various programs stored in the auxiliary storage unit  604 . Specifically, the ROM  602  stores a boot program or the like such as the BIOS or the EFI. 
     The RAM  603  is a volatile memory such as the DRAM or the SRAM, and acts as the main storage unit. The RAM  603  provides the working area to be expanded when the CPU  601  executes the various programs stored in the auxiliary storage unit  604 . 
     The auxiliary storage unit  604  stores installed various programs or information to be used when the various programs are executed. The communication unit  605  is a device for communicating with the image generation device  110 . 
     The operation unit  606  is a device for inputting various instructions to the HMD. The display unit  123  is a device for displaying images in the virtual space included in the virtual space information transmitted from the image generation device  110 . 
     The head posture sensor  124  senses “head position and orientation” included in the non-verbal action of the user  140  (illustrated in  FIG. 1 ) in the real space and outputs the head posture data. 
     The I/F unit  607  connects with the depth sensor  125  and the muscle potential sensor  126 , acquires the depth sensor data outputted from the depth sensor  125  and the muscle potential data outputted from the muscle potential sensor  126 . 
     The sensor data acquired, such as the head posture data, the depth sensor data, and the muscle potential data, are transmitted to the image generation device  110  by the communication unit  605 . Note that although an example of  FIG. 6  illustrates a case where the HMD is formed as an integral device, the HMD may be integrally formed or may be formed by a plurality of separate devices. 
     &lt;Overview of Presentation Control Processing of Reactive Processing Unit&gt; 
     In the following, description is given of an overview of the presentation control processing implemented by the reactive processing unit  115  of the image generation device  110 .  FIG. 7  is a diagram illustrating the overview of the presentation control processing of the reactive processing unit of the image generation device. 
     In  FIG. 7 , of three solid lines extending from the image generation device  110 , the first solid line indicates a timing when the reactive processing unit  115  generates the image of the avatar of the user  150  in order to present reactive social behavior to the user  140 . In addition, the second solid line indicates the timing when the basic function unit generates the avatar image and generates the virtual space information, based on the sensor data obtained by sensing actions of the users  140  and  150 , respectively. Furthermore, the third solid line indicates the timing when the basic function unit receives the sensor data obtained by sensing the actions of the users  140  and  150 , respectively. 
     In  FIG. 7 , of two lines extending from the client-side systems  120 ,  130 , the first solid line indicates the timing when the client-side systems  120 ,  130  receive the virtual space information. In addition, the second solid line indicates the timing when the client-side systems  120 ,  130  collect the sensor data. 
     Note that in  FIG. 7 , rectangular graphics placed on the solid lines to indicate the respective timings include graphics a height of which in a vertical direction is high and the graphics the height of which in the vertical direction is low. The former represents data related to a group of images and the latter represents data other than the group of images. 
     As illustrated in  FIG. 7 , when the client-side system  120  collects sensor data  710  corresponding to the social behavior of the user  140  to the user  150 , the client-side system  120  transmits the collected sensor data  710  to the image generation device  110 . 
     The basic function unit of the image generation device  110  generates a virtual space image  7101  by generating an image of the avatar of the user  140  based on the sensor data  710  received from the client-side system  120  and incorporating the generated image of the avatar. The basic function unit of the image generation device  110  also transmits the generated virtual space image  7101  to the client-side systems  120 ,  130 . 
     At this time, the reactive processing unit  115  of the image generation device  110  generates an image  720  of the avatar and notifies the basic function unit of the image, in order to present to the user  140  the reactive social behavior of the user  150  to the social behavior of the user  140 . 
     With this, the basic function unit of the image generation device  110  generates a virtual space image  7201  incorporating the image  720  of the avatar and transmits the virtual space image  7201  to the client-side system  120 . 
     This enables the client-side system  120  to receive and display the virtual space image  7201  immediately after receiving and displaying the virtual space image  7101 . As described above, the virtual space image  7101  includes the image of the avatar responding to the social behavior of the user  140 , and the virtual space image  7201  includes the image  720  of the avatar representing the reactive social behavior of the user  150 . Thus, the client-side system  120  may present the reactive social behavior of the user  150  to the user  140  (The presentation of the reactive social behavior of the user  150  may be controlled to a time lag depicted by an arrow  2510 ). 
     On the other hand, the client-side system  130  receives and displays the virtual space image  7101 . With this, the user  150  performs some social behavior and the client-side system  130  collects corresponding sensor data  730  and transmits the sensor data  730  to the image generation device  110 . 
     The basic function unit of the image generation device  110  generates a virtual space image  7301  by generating an image of the avatar of the user  150  based on the sensor data  730  received from the client-side system  130  and incorporating the generated avatar image. The basic function unit of the image generation device  110  also transmits the generated virtual space image  7301  to the client-side system  130 . 
     At this time, suppose that as with a conventional communication system, the virtual space image  7301  is also transmitted to the client-side system  120 . In this case, the client-side system  120  receives the virtual space image  7101  and then displays the virtual space image  7301 , with the time lag of an arrow  2520 . 
     As described above, the virtual space image  7101  includes the image of the avatar corresponding to the social behavior of the user  140 , and the virtual space image  7301  includes the image of the avatar corresponding to the social behavior of the user  150 . Thus, in the conventional communication system, the social behavior of the user  150  is presented to the user  140 , with the time lag of the arrow  2520 , and reactive presentation is not possible. 
     In contrast to this, as described above, with the reactive processing unit  115 , the time lag may be controlled to the time lag of the arrow  2510  and shortened by time duration depicted by the arrow  2530 . More specifically, the social behavior which is more reactive than usual may be presented to the user  140 . 
     &lt;Functional Configuration of Reactive Processing Unit of Image Generation Device&gt; 
     In the following, description is given of a functional configuration of the reactive processing unit  115  of the image generation device  110 .  FIG. 8  is a first diagram illustrating the functional configuration of the reactive processing unit of the image generation device. As illustrated in  FIG. 8 , the reactive processing unit  115  includes a social behavior log recording section  801 , a social behavior value calculation section  802 , an approach and avoidance tendency identification section  803 , a dialogue strategy determination section  804 , and a presentation control section  805 . 
     The social behavior log recording section  801  monitors a “log table relating to avatar display information” stored in the log DB  117 . Note that as described above, the “log table relating to avatar display information” is a table recording, as log data, data used when the basic function unit of the image generation device  110  generates the avatar image, based on the respective tables stored in the sensor data DB  116   b.    
     When monitoring the “log table relating to avatar display information”, the social behavior log recording section  801  refers to a “monitoring target data log definition data table” stored in the definition data DB  118  and identifies the avatar skeleton and an update threshold of the part targeted for monitoring. 
     In addition, of log data included in the “log table relating to avatar display information”, the social behavior log recording section  801  identifies log data for which a change in the positional coordinates and the rotation angle of the avatar skeleton of the part targeted for the part exceeds the update threshold. In addition, the social behavior log recording section  801  records the identified log data in a “behavior log update recording table” of the evaluation information DB  119 . 
     Note that the social behavior log recording section  801  may also refer to the “behavior log update recording table” stored in the evaluation information DB  119 , in addition to the “log table relating to avatar display information” stored in the log DB  117 . This is because the “behavior log update recording table” records the positional coordinates and the rotation angle at previous time points of the avatar skeleton of the part targeted for monitoring. 
     Furthermore, the social behavior log recording section  801  judges whether or not the identified log table corresponds to the social behavior. If so, the social behavior log recording section  801  records the identified log data in the “social behavior log recording table”. 
     Note that when judging whether or not the identified log data corresponds to the social behavior, the social behavior log recording section  801  uses an API defined in a social behavior judgment API definition data table of the definition data DB  118 . The API stands for Application Programming Interface and acts as a library to judge the social behavior. 
     The social behavior value calculation section  802  calculates or identifies various information relating to the social behavior, for each log data recorded in the “social behavior log recording table”. The various information relating to the social behavior includes—intensity of the social behavior, —an attribute value of the social behavior, —information indicating approach tendency and avoidance tendency of the social behavior, —whether or not there is a touch on a body part by the social behavior, —whether or not an expression is presented due to the social behavior, —whether or not there is a touch on the body part due to reception of the social behavior, —whether or not there the expression is presented due to the reception of the social behavior, or the like. Of the above, in the first embodiment, the information indicating the social behavior approach tendency and the avoidance tendency is used in determining a dialogue strategy (information for identifying practicable behavior or behavior practice of which be avoided). The information indicating the social behavior approach tendency and the avoidance tendency is information indicating whether each log data indicates the social behavior of the approach tendency or the social behavior of the avoidance tendency. The social behavior value calculation section  802  identifies the social behavior tendency by referring to the “social behavior approach and avoidance tendency definition data table”, for example. 
     The social behavior value calculation section  802  also records various information relating to the social behavior in a “social behavior value calculation recording table” of the evaluation information DB  119 . 
     Note that among the various information relating to the social behavior, which is calculated or identified by the social behavior value calculation section  802 , any information other than the information indicating the social behavior approach tendency and the avoidance tendency shall be used in determining the dialogue strategy, in a second embodiment. 
     The approach and avoidance tendency identification section  803  is an example of the identification section. The approach and avoidance tendency identification section  803  judges the social behavior tendency to the dialogue partner in a predetermined temporal interval, based on the “social behavior value calculation recording table”. Specifically, the approach and avoidance tendency identification section  803  identifies the social behavior tendency to the dialogue partner by referring to information indicating the “social behavior approach tendency and avoidance tendency” in the predetermined temporal interval recorded in the “social behavior value calculation recording table”. 
     The dialogue strategy determination section  804  is an example of the determination section. The dialogue strategy determination section  804  determines the dialogue strategy which is an example of a communication strategy to the dialogue partner, based on the social behavior to the dialogue partner, identified by the approach and avoidance tendency identification section  803 . 
     The presentation control section  805  is an example of the control section. If it is judged that user  140  performs the social behavior to the user  150 , for example, the presentation control section  805  judges whether the reactive social behavior is permitted for the determined dialogue strategy (dialogue strategy of the user  150  to the user  140 ). Note that in judging whether or not the reactive social behavior is permitted, the presentation control section  805  refers to a “control definition data table on whether reactive social behavior for dialogue strategy is permitted” of the definition data DB  118 . 
     If the presentation control section  805  judges that the reactive social behavior is permitted, the presentation control section  805  also generates the avatar image indicating the reactive social behavior of the user  150 , which is associated with the determined dialogue strategy, and transmits the avatar image to the information display processing section  112  (illustrated in  FIG. 1 ). In addition, the presentation control section  805  instructs the information display processing section  112  to display the avatar image indicating the reactive social behavior of the user  150 . Furthermore, the presentation control section  805  records the dialogue strategy of this time in a “dialogue strategy determination recording table” of the evaluation information DB  119 . 
     &lt;Description of Table Relating to Processing of Respective Components of Reactive Processing Unit&gt; 
     In the following, description is given of respective tables relating to processing of the respective components (social behavior log recording section  801  to the presentation control section  805 ) of the reactive processing unit  115 . 
     (1) Respective Tables of the Sensor Data DB  116   b    
       FIGS. 9A to 9C  are diagrams illustrating examples of the respective tables stored in the sensor data DB. Of the examples,  FIG. 9A  illustrates a muscle potential data table  900  in which the muscle potential data is stored. As illustrated in  FIG. 9A , the muscle potential data table  900  in which the muscle potential data is stored includes, as an information item, “DB recording time”, “sensor recording time”, “user ID”, “information collector ID”, and “muscle potential activity value (or EMG value)”. 
     In the “DB recording time” is recorded a time stamp to be added when the muscle potential data transmitted from the client-side systems  120 ,  130  is stored in the sensor data DB  116   b.    
     In the “Sensor recording time” is recorded the time stamp added when the muscle potential sensors  126 ,  136  sense the users  140 ,  150 . 
     In the “User ID” is recorded an identifier identifying the users  140 ,  150  sensed by the muscle potential sensors  126 ,  136 . 
     In the “Information collector ID”, the identifier identifying the muscle potential sensor is recorded. The muscle potential sensor has the identifier that varies depending on a location where the sensing takes place. Of data rows in  FIG. 9A , “TcA_c3_zygomaticus (check)” on a first row is the identifier of the muscle potential sensor that senses cheeks. In addition, of the data rows in  FIG. 9A , “TcA_c3_orbicularis (under eye)” on a second row is the identifier of the muscle potential sensor that senses an under eye area. Furthermore, of the data rows in  FIG. 9A , “TcA_c3_corrugator (blow)” on a third row is the identifier of the muscle potential sensor that senses an eyebrow. 
     In the “Muscle potential activity value” are recorded values of the muscle potential data sensed by the respective muscle potential sensors. 
       FIG. 9B  illustrates a head posture data table  910  in which the head posture data is stored. As illustrated in  FIG. 9B , items of information included in the head posture data table  910  are roughly same as the items of information included in the muscle potential data table  900 . 
     Note that in the “information collector ID” in the head posture data table  910 , “TcA_c1” indicates that the information processor with the information processor ID of “TcA” is associated with the information collector of the information collector type “c1”. Specifically, “TcA_c1” is the head posture sensor  124  associated with the information processor  121 . 
     In addition, in the “header posture data”, data representing the positional coordinates of the head and data representing the rotation angle of the head are recorded. 
       FIG. 9C  illustrates a depth sensor data file table  920  in which the depth sensor data is stored. As illustrated in  FIG. 9C , the “depth sensor data file table”  920  includes, as the information item, the “DB recording time”, the “user ID”, and the “information collector ID”, similar to other sensor data tables. In addition, the “depth sensor data file table”  920  includes, as the information item, “sensor recording start time”, “sensor recording end time”, and “depth sensor data recording file URI”. 
     In the “sensor recording start time”, time when the depth sensors  125 ,  135  start sensing is recorded. In the case of the depth sensors  125 ,  135 , the sensor data is outputted as a file of a predetermined recording length. Thus, in the “sensor recording start time” is recorded the time stamp added when the first depth sensor data included in each file is sensed. 
     In the “sensor recording end time” is recorded time when the sensing by the depth sensors  125 ,  135  (illustrated in  FIG. 1 ) ends. Specifically, the time stamp added when the last depth sensor data included in the file of the predetermined recording length is sensed is recorded. 
     In the “depth sensor data recording file URI” is recorded an URI representative of a location where the file having the predetermined recording length is stored. 
     Note that in the “information collector ID” in the “depth sensor data file table”  920 , “TcA_c2” indicates that the information processor with the information processor ID of “TcA” is associated with the information collector of the information collector type “c2”. Specifically, “TcA_c2” represents the depth sensor  125  associated with the information processor  121 . 
     (2) Tables of Log DB  117   
       FIG. 10  is a diagram illustrating an example of the log table relating to avatar display information stored in the log DB. A “log table relating to avatar display information”  1000  records data (positional coordinates and the rotation angle of the respective avatar skeletons) used in generating the avatar image as the log data. 
     As illustrated in  FIG. 10 , the “log table relating to avatar display information”  1000  includes, as the information item, the “DB recording time”, “user current time”, the “user ID”, “information processor ID”, “log type label”, and “log data of avatar display information”. 
     In the “DB recording time” is recorded time when the data used in generating the avatar image is recorded, as the log data, in the “log table relating to avatar display information”  1000 . 
     In the “user current time”, time when the user performs the non-verbal action corresponding to the log data is recorded. In the “user ID”, the identifier identifying the user who performs the non-verbal action is recorded. 
     In the “information processor ID” is recorded the identifier identifying the information processor that manages the user who performs the non-verbal action. 
     In the “log type label”, information indicating a method of expression in generating the avatar image is recorded. In an example of  FIG. 10 , “bone” indicating that the non-verbal action is expressed through the use of the avatar skeleton model and “mesh” indicating that the non-verbal action is expressed through the use of a mesh are recorded. 
     In the “log data of avatar display information”, the data used in generating the avatar image is recorded as a structured list. 
     An example of the first row of the data rows in  FIG. 10  indicates that as a result of the user  140  with the user ID=“userA” performing the non-verbal action at “11:00:00:000 on Jul. 27, 2015”, the positional coordinates of the avatar skeleton of the head becomes (0, 18, −10). In addition, the example also indicates that the rotation angle of the avatar skeleton of the head becomes (0, 1, 0). The example also indicates that the log data of the avatar display information including the positional coordinates and the rotation angle are recorded in the in the log DB  117  at “11:00:00:020 on Jul. 27, 2015”. 
     (3) Respective Tables of the Definition Data DB  118   
     In the following, description is given of the respective tables stored in the definition data DB  118 . 
     (3-1) Monitoring Target Data Log Definition Data Table 
       FIG. 11  is a diagram illustrating an example of the monitoring target data log definition data table stored in the definition data DB. As illustrated in  FIG. 11 , the “monitoring target data log definition data table”  1100  includes, as the information item, “behavior log type label”, “update threshold”, “update monitoring target”, “sensor input information”, and the “information collector ID”. 
     The “behavior log type label” defines a type of behavior of the part targeted for monitoring when the social behavior log recording section  801  (illustrated in  FIG. 8 ) monitors the “log table relating to avatar display information”  1000  (illustrated in  FIG. 10 ) and the “behavior log update recording table”  1600  (illustrated in  FIGS. 16A-16D ). 
     The “update monitoring target” defines the threshold to be used when the social behavior log recording section  801  judges whether or not the log data stored in the “log table relating to avatar display information”  1000  or the like is to be recorded in the “behavior log update recording table”. 
     The “update monitoring target” defines a specific avatar skeleton for monitoring a type of the behavior of the part defined in the “behavior log type label”. 
     The “sensor input information” defines a type of the sensor data for identifying the positional coordinates and the rotation angle of the avatar skeleton of the part defined for the “update monitoring target”. The “information collector ID” defines the identifier for identifying the sensor used to collect the sensor data defined in the “sensor input information”. 
     In an example on the first row of the data rows of  FIG. 11 , the avatar skeleton is targeted for monitoring, the avatar skeleton being calculated based on the depth sensor data sensed by the depth sensor which is identified by the identifier=“TcA_c2”. Specifically, the avatar skeleton (Bone_Head, Bone_Righthand, and Bone_Lefthand) of the head or a right arm or a left arm is targeted for monitoring. 
     The social behavior log recording section  801  refers to the “log table relating to avatar display information”  1000  and the “behavior log update recording table”  1600 , described below. Then, the social behavior log recording section  801  judges whether or not the change in the positional coordinates (X coordinate, Y coordinate, and Z coordinate) of any of the avatar skeletons of these avatar skeletons is larger than “1”. This enables the social behavior log recording section  801  to monitor the behavior that changes the physical distance of the body parts (Distance_Bodyparts) in the virtual spaces of the image  220  of the avatar of the user  140  and the image  230  of the avatar of the user  150 . Here, the social behavior log recording section  801  may monitor the behavior that changes the physical distance of the head, the right arm, and the left arm. 
     (3-2) Social Behavior Judgment API Data Table 
       FIG. 12  is a diagram illustrating an example of a social behavior judgment API definition data table stored in the definition data DB. The “social behavior judgment API definition data table”  1200  is a table to be used in judging whether or not the log data recorded in the “behavior log update recording table” by the social behavior log recording section  801  (illustrated in  FIG. 8 ) corresponds to the social behavior. 
     As illustrated in  FIG. 12 , the social behavior judgment API definition data table  1200  includes, as the information item, “social behavior type label”, “social behavior judgment API”, and “behavior log type label”. 
     The “social behavior type label” defines a type of the social behavior judged by the social behavior judgment API. The “social behavior judgment API” defines the API to be used in judging the social behavior. The API to be used in judging the social behavior is defined depending on the “behavior log type label” in the “monitoring target data log definition data table”  1100  (illustrated in  FIG. 11 ). 
     Thus, the “social behavior judgment API” is associated with the “behavior log type label” and defined. The “behavior log type label” defines the type of the behavior defined in the “monitoring target data log definition data table”  1100 . 
     An example on the fifth row of the data rows of  FIG. 12  indicates that for the log data for which the change in the physical distance of the body parts (Distance_Bodyparts) is more than the update threshold, the social behavior log recording section  801  judges the type of social behavior. According to the example, the social behavior log recording section  801  uses movement confirmation API to judge whether or not the log data corresponds to the social behavior (Distance_Bodyparts_Closeto). 
     (3-3) Social Behavior Approach and Avoidance Tendency Definition Data Table 
       FIG. 13  is a diagram illustrating an example of the social behavior approach and avoidance tendency definition data table stored in the definition data DB. The “social behavior approach and avoidance tendency definition data table”  1300  is used when the social behavior value calculation section  802  (illustrated in  FIG. 8 ) judges whether the social behavior judged by the social behavior log recording section  801  is the approach tendency or the avoidance tendency. 
     As illustrated in  FIG. 13 , the “social behavior approach and avoidance tendency definition data table”  1300  includes “social behavior log type label” and “approach and avoidance tendency”, as the information item. 
     The “social behavior log type label” defines the type of social behavior (all of the social behavior types defined in the “social behavior judgment API definition data table”  1200  are defined). The “approach and avoidance tendency” defines any of the approach tendency or the avoidance tendency for the type of each social behavior. 
     An example on the fifth row of the data rows of  FIG. 13  indicates that if the social behavior type is the “Distance_Bodyparts_Closeto”, the social behavior value calculation section  802  judges that the social behavior is the social behavior of the approach tendency. 
     Note that the respective records stored in the “social behavior log type label” of the “social behavior approach and avoidance tendency definition data table”  1300  mean the following actions. 
     For example, “Distance_Upperbody_Closeto” refers to an action to move an upper body to a partner, and “Distance_Upperbody_Farfrom” refers to an action to move the upper body away from the partner. In addition, “Distance_Face_Closeto” refers to an action to move a face to the partner, and “Distance_Face_Farfrom” refers to an action to move the face away from the partner. 
     In addition, “Distance_Bodyparts_Closeto” refers to an action to move the body part close to the partner and “Distance_Bodyparts_Farfrom” refers to an action to move the body part away from the partner. “Attention_Mutual” refers to an action to pay attention to each other and “Attention_Averted” refers to an action to avert the attention. 
     In addition, “Attention_Joint” refers to an action to pay attention to a same object as the partner does, and “Attention_Following” refers to an action to pay attention following the partner paying attention. “Orientation_Face_Directto” refers to an action to turn a face to a direction in which the partner is present, and “Orientation_Face_Indirectto” refers to an action to turn the face to a direction opposite to the direction in which the partner is present. 
     In addition, “Orientation_Upperbody_Directto” refers to an action to turn the upper body to a direction in which the partner is present, and “Orientation_Upperbody_Indirectto” refers to an action to turn the upper body to the direction opposite to the direction in which the partner is present. “Lean_Upperbody_Forward” refers to an action to lean the upper body forward, and “Lean_Upperbody_Backward” refers to an action to lean the upper body backward. 
     In addition, “Gesture_Smileto” refers to an action to smile. Furthermore, “Gesture_Positivemeaninggestureto” refers to an action to give a positive sign, and “Gesture_Negativemeaninggestureto” refers to an action to give a negative sign. 
     (3-4) Control Definition Data Table on Whether Reactive Social Behavior for Dialogue Strategy is Permitted 
       FIG. 14  is a diagram illustrating an example of a control definition data table on whether a reactive social behavior for a dialogue strategy is permitted, stored in the definition data DB. The “control definition data table on whether reactive social behavior for dialogue strategy is permitted”  1400  is used when the presentation control section  805  (illustrated in  FIG. 8 ) judges whether or not the reactive social behavior is permitted. 
     As illustrated in  FIG. 14 , the “control definition data table on whether reactive social behavior for dialogue strategy is permitted”  1400  includes, as the information item, “permission control condition ID”, “permission control condition”, and “implementation flag”. 
     The “permission control condition ID” defines the identifier for identifying a permission control condition. The “permission control condition” defines a condition for permitting presentation to the dialogue partner of the reactive social behavior to the dialogue strategy. The “implementation flag” defines information indicating whether or not the permission based on the corresponding “permission control condition” is given. 
     In an example of  FIG. 14 , two conditions are defined as the “permission control condition”. In the case of the permission control condition identified by a permission control condition ID=“1”, presentation of the reactive social behavior to the dialogue partner is not permitted even in any dialogue strategy. However, the presentation of the reactive social behavior starting with “shortly” to the dialogue partner is permitted. 
     In the case of the permission control condition identified by the permission control condition ID=“2”, the presentation of the reactive social behavior to the dialogue partner is permitted in any dialogue strategy. However, the presentation of the reactive social behavior starting with “Enforcing_Totally” to the dialogue partner is not permitted. 
     Note that in the example of  FIG. 14 , the “implementation flag” of the permission control condition ID=“1” is “TRUE”, and the “implementation flag” of the permission control condition ID=“2” is “FALSE”. Thus, in the case of the example of the  FIG. 14 , the presentation control section  805  controls whether or not to present to the dialogue partner the reactive social behavior, based on the permission control condition of the permission control condition ID=“1”. 
     &lt;Details of Presentation Control Processing of Reactive Processing Unit&gt; 
     In the following, detailed description is given of the presentation control processing of the reactive processing unit  115  (illustrated in  FIG. 1 ).  FIG. 15  is a first flowchart illustrating details of the presentation control processing of the reactive processing unit. The presentation control processing illustrated in  FIG. 15  is started when the users  140  and  150  (illustrated in  FIG. 1 ) start to utilize the communication service and the log data is stored in the “log table relating to avatar display information”  1000  (illustrated in  FIG. 10 ). Meanwhile, in the following, although it is described that the dialogue strategy is determined every time the presentation control processing is performed, the dialogue strategy may be determined for every predetermined period or whenever a certain amount of the social behavior recorded. 
     In step S 1501 , the social behavior log recording section  801  (illustrated in  FIG. 8 ) reads out the “log table relating to avatar display information”  1000  and the “behavior log update recording table”  1600  (illustrated in  FIGS. 16A-16D ) described below. 
     In step S 1502 , the social behavior log recording section  801  monitors the log data in the “log table relating to avatar display information”  1000 , based on the “monitoring target data log definition data table”  1100  (illustrated in  FIG. 11 ), or the like. In addition, if the log data exceeding the update threshold is detected, the social behavior log recording section  801  records the log data in the “behavior log update recording table” of the evaluation information DB  119 .  FIGS. 16A to 16D  are diagrams illustrating an example of the behavior log update recording table recorded in the evaluation information DB. Note that details of the “behavior log update recording table”  1600  illustrated in  FIGS. 16A and 16D  are described below. 
     Furthermore, the social behavior log recording section  801  judges whether or not the log data recorded in “behavior log update recording table”  1600  corresponds to the social behavior. If so, the social behavior log recording section  801  judges a type of the social behavior, using the social behavior judgment API. Additionally, the social behavior log recording section  801  determines any of which social behavior judgment API is used, by referring to the “social behavior judgment API definition data table”  1200  (illustrated in  FIG. 12 ). 
     Furthermore, the social behavior log recording section  801  records the log data judged to correspond to the social behavior together with the judged type of the social behavior in the “social behavior log recording table” in the evaluation information DB.  FIG. 17  is a diagram illustrating an example of the social behavior log recording table recorded in the evaluation information DB. Note that details of the “social behavior log recording table”  1700  illustrated in  FIG. 17  are described below. 
     In step S 1503 , the social behavior value calculation section  802  calculates or identifies various information relating to the social behavior judged by the social behavior log recording section  801 . 
     Specifically, the social behavior value calculation section  802  calculates or identifies, as the various information relating to the social behavior, intensity of the social behavior, the attribute value of the social behavior, continued seconds of the social behavior, and approach and avoidance tendency of the social behavior. Additionally, when identifying the approach and avoidance tendency of the social behavior, the social behavior value calculation section  802  refers to the “social behavior approach and avoidance tendency definition data table”  1300  (illustrated in  FIG. 13 ). 
     Furthermore, the social behavior value calculation section  802  calculates, as the various information relating to the social behavior, information disclosure by the non-verbal action (whether or not there is a touch on the body) and presentation of the information disclosure by the non-verbal action (whether or not the intention and the demeanor (expression or the like) are presented). 
     Furthermore, the social behavior value calculation section  802  calculates, as the various information relating to the social behavior, information disclosed by the non-verbal action (whether or not there is the touch on the body) and presentation of the information disclosed by the non-verbal action (whether or not an intention and a demeanor (expression or the like) are presented). 
     The social behavior value calculation section  802  records the calculated or identified various information relating to the social behavior in the “social behavior value calculation recording table”.  FIGS. 18A and 18B  are diagrams illustrating an example of the social behavior value calculation recording table recorded in the evaluation information DB. Note that details of the “social behavior value calculation recording table”  1800  illustrated in  FIGS. 18A and 18B  are described below. 
     In step S 1504 , the approach and avoidance tendency identification section  803  refers to the “social behavior value calculation recording table”  1800 . As described above, in the first embodiment, the dialogue strategy is determined based on the “social behavior approach and avoidance tendency” recorded in the various information record in the “social behavior value calculation recording table”  1800 . 
     Then, the approach and avoidance tendency identification section  803  refers to the log data that is the log data in the predetermined temporal interval and has a behaving avatar ID=“AV 2 ” and a behaved avatar ID=“AV 1 ”, in the “social behavior value calculation recording table”  1800 . The approach and avoidance tendency identification section  803  identifies whether tendency of the social behavior of the user  150  to the user  140  in the predetermined temporal interval is the approach tendency or the avoidance tendency. 
     In step S 1505 , the dialogue strategy determination section  804  determines the dialogue strategy. Specifically, the dialogue strategy determination section  804  determines the dialogue strategy of the user  150  to the user  140  based on the identified tendency. 
     In step S 1506 , the presentation control section  805  refers to the “control definition data table on whether reactive social behavior for dialogue strategy is permitted”  1400  (illustrated in  FIG. 14 ). With this, the presentation control section  805  judges whether or not presentation of the reactive social behavior for the determined dialogue strategy to the user  140  is permitted. 
     If the presentation control section  805  judges that the presentation is permitted, the presentation control section  805  controls to generate the avatar image based on the reactive social behavior associated with the determined dialogue strategy and present to the user  140 . Note that in the first embodiment, the reactive social behavior associated with the dialogue strategy is predefined. 
     Furthermore, the presentation control section  805  records the determined dialogue strategy in the “dialogue strategy determination recording table” of the evaluation information DB  119  (illustrated in  FIG. 8 ).  FIG. 19  is a diagram illustrating an example of the dialogue strategy determination recording table recorded in the evaluation information DB. Note that details of the “dialogue strategy determination recording table”  1900  illustrated in  FIG. 19  are described below. 
     &lt;Description of Table Recorded by Reactive Processing Unit&gt; 
     In the following, description is given of the respective tables recorded in the evaluation information DB  119  that are recorded as the reactive processing unit  115  performs the presentation control processing ( FIG. 15 ). 
     (1) Behavior Log Update Recording Table  1600 . 
     First, the “behavior log update recording table”  1600  of  FIGS. 16A-16D  is described. As illustrated in  FIGS. 16A-16D , the “behavior log update recording table”  1600  includes, as the information item, the “DB recording time”, “recording start time”, “recording update time”, the “behaving avatar ID”, the “behavior log type label”, and the “update monitoring target”. The “behavior log update recording table”  1600  also includes, as the information item, “update status”, “data at recording start”, “data at recording update”, and “social behavior log recording ID reference value”. 
     In the “DB recording time” is recorded time when the social behavior log recording section  801  (illustrated in  FIG. 8 ) records in the “behavior log update recording table”  1600  that there is the log data exceeding the update threshold. 
     In the “recording start time” is recorded time when the user starts to record the non-verbal action corresponding to the log data exceeding the update threshold. 
     In the “recording update time” is recorded time when the user performs the corresponding non-verbal action corresponding to the log data at the time when the log data exceeds the update threshold. 
     In the “behavior avatar ID” is recorded the avatar identifier of the user who performs the non-verbal action corresponding to the log data exceeding the update threshold. 
     In the “behavior log type label” is recorded the type of the behavior of the part targeted for monitoring when the social behavior log recording section  801  monitors the “log table relating to avatar display information”  1000  (illustrated in  FIG. 10 ) or the like. 
     In the “update monitoring target” is recorded the specific avatar skeleton used to monitor the type of the behavior of the part recorded in the “behavior log type label”. 
     In the “update status” is recorded a result of a comparison with the update threshold. If a difference between the log data at the previous time and the log data at the present time exceeds the update threshold, “change being recorded” is recorded in the “update status”. On the other hand, if the difference between the log data at the previous time and the log data at the present time does not exceed the update threshold, “no change record” is recorded in the “update status”. Note that for the avatar skeleton of the part targeted for monitoring, as long as “change being recorded” continues, same time is recorded in the “recording start time”. 
     If the log data exceeding the update value is the log data for which the positional coordinates or the rotation angle of the avatar skeleton of the part targeted for monitoring are in change being recorded, in the “data at recording start” are recorded the positional coordinates and the rotation angle of when the change recording starts. 
     If the log data exceeding the update threshold is the log data for which the positional coordinates or the rotation angle of the avatar skeleton of the part targeted for monitoring are in change being recorded, in the “data at recording update” are recorded the positional coordinates and the rotation angle of when the record is updated. 
     In the “social behavior log recording ID reference value” is recorded the identifier for referring to the record on the database of the social behavior log data, if the social behavior log recording section  801  judges that the log data exceeding the update threshold corresponds to the social behavior. 
     (2) Social Behavior Log Recording Table  1700   
     In the following, the “social behavior log recording table”  1700  of  FIG. 17  is described. As illustrated in  FIG. 17 , the “social behavior log recording table”  1700  includes, as the information item, the “DB recording time”, the “recording start time”, the “recording end time”, the “behaving avatar ID”, and the “behaved avatar ID”. The “social behavior log recording table”  1700  also includes, as the information item, the “social behavior log recording ID”, the “social behavior type label”, and the “social behavior log type label”. 
     In the “DB recording time” is recorded time when the log data recorded in the “social behavior log update recording table”  1600  (illustrated in  FIGS. 16A-16D ) is judged to correspond to the social behavior and recorded in the “social behavior log recording table”  1700 . 
     In the “recording start time” is record time when the user starts the non-verbal action corresponding to the log data judged to correspond to the social behavior. 
     In the “recording end time” is recorded time when the user ends the non-verbal action corresponding to the log data judged to correspond to the social behavior. 
     In the “behaving avatar ID” is recorded the identifier identifying the avatar of the user who performs the social behavior. 
     In the “behaved avatar ID” is recorded the identifier identifying the avatar of the user who receives the social behavior. 
     In the “social behavior log recording ID” is recorded the identifier for identifying the log data of the judged social behavior. 
     In the “social behavior type label” is recorded the type of the judged social behavior. In the “behavior log type label” is recorded the type of the behavior indicated by the log data judged to corresponding to the social behavior. 
     (3) Social Behavior Value Calculation Recording Table  1800   
     In the following, the “social behavior value calculation recording table”  1800  of  FIGS. 18A-18B  is described. As illustrated in  FIGS. 18A-18B , the “social behavior value calculation recording table”  1800  includes, as the information item, the “DB recording time”, the “recording start time”, the “recording end time”, the “behaving avatar ID”, the “behaved avatar ID”, and the “social behavior log recording ID”. 
     The “social behavior value calculation recording table”  1800  also includes, as the information item, the “social behavior type label”, “intensity of social behavior”, and “attribute value of social behavior”. 
     The “social behavior value calculation recording table”  1800  also includes “continued seconds of social behavior” and “social behavior approach and avoidance tendency”, as the information item. 
     The “social behavior value calculation recording table”  1800  also includes, as the information item, “information disclosure by non-verbal action (whether or not there is touch on body)” and “information disclosure by non-verbal action (whether or not intention and demeanor (expression or the like) are presented)”. 
     The “social behavior value calculation recording table”  1800  also includes, as the information item, “information disclosed by non-verbal action (whether or not there is touch on body)” and “information disclosed by non-verbal action (whether or not intention and demeanor (expression or the like) are presented)”. 
     Of these information items, when the respective information items are viewed in a direction from the left to the right of  FIGS. 18A-18B , the respective information items from the “DB recording time” from the “social behavior type label” are similar to the respective information items included in the “social behavior log recording table”  1700  (illustrated in  FIG. 17 ). Thus, description is omitted. Here, description is given of the various information relating to the social behavior when the respective information items are viewed in the direction from the left to the right of  FIGS. 18A-18B . That is, description is given of information recorded in the respective information items from the “intensity of social behavior” to the “information disclosed by non-verbal action (whether or not intention and demeanor (expression or the like) are presented)”. 
     In the “intensity of social behavior” is recorded a numeric value representing the intensity of the social behavior. In the “attribute value of social behavior” is recorded an amount of change in the physical distance or the amount of change in the rotation angle that are calculated when it is judged whether or not to correspond to the social behavior. 
     In the “continued seconds of social behavior” is recorded the continued time (seconds) of the log data judged to correspond to the social behavior. 
     In the “social behavior approach and avoidance tendency” is recorded a result of judgment that judges whether the social behavior is the social behavior of the approach tendency or the social behavior of the avoidance tendency. 
     In the “information disclosure by non-verbal action (whether or not there is touch on body)” is recorded information indicating whether or not the avatar of the user who performs the social behavior by performing the non-verbal action touches the avatar of the user who receives the social behavior. 
     In the “information disclosure by non-verbal action (whether or not intention and demeanor (expression or the like) are presented)” is recorded information indicating whether or not the expression or the like of the avatar of the user who performs the social behavior by performing the non-verbal action is presented to the user who receives the social behavior. 
     In the “information disclosed by non-verbal action (whether or not there is touch on body)” is recorded information indicating whether or not the avatar of the user who receives the social behavior is touched by the avatar of the user who performs the social behavior by performing the non-verbal action. 
     In the “information disclosed by non-verbal action (whether or not intention and demeanor (expression or the like) are presented)” is recorded information indicating whether or not the user who receives the social behavior is presented with the expression or the like of the avatar of the user who performs the social behavior by performing the non-verbal action. 
     (4) Dialogue Strategy Determination Table  1900   
     In the following, the “dialogue strategy determination recording table”  1900  of  FIG. 19  is described. As illustrated in  FIG. 19 , the “dialogue strategy determination recording table”  1900  includes, as the information item, the “DB recording time”, the “behaving avatar ID”, the “behaved avatar ID” and the “dialogue strategy”. 
     In the “DB recording time” is recorded time when the presentation control section  805  (illustrated in  FIG. 8 ) records in the “dialogue strategy determination recording table”  1900  the dialogue strategy to be used to control so as to present the reactive social behavior to the dialogue partner. 
     In the “behaving avatar ID” and the “behaved avatar ID” are respectively recorded the user&#39;s avatar ID. In the “dialogue strategy” is recorded the dialogue strategy by the user of the avatar ID recorded in the “behaving avatar ID” to the user of the avatar ID recorded in the “behaved avatar ID”. 
     As is clear from the foregoing description, the image generation device  110  according to the first embodiment includes the reactive processing unit  115  and monitors the log table in the “log table relating to avatar display information” and “behavior log update recording table” generated by the basic function unit (each illustrated in  FIG. 1 ). In addition, when the first user (user  140 ) performs the social behavior to the second user (user  150 ), the reactive processing unit  115  identifies the tendency of the social behavior in the predetermined temporal interval that is performed by the second user to the first user (each illustrated in  FIG. 1 ). The reactive processing unit  115  also determines the dialogue strategy of the second user to the first user based on the identified tendency. 
     Furthermore, if the first user performs the social behavior to the second user after the dialogue strategy is determined, the reactive processing unit  115  controls so that the reactive social behavior by the second user based on the determined dialogue strategy is presented to the first user. 
     Accordingly, with the image generation device  110  according to the first embodiment, if the first user performs the social behavior to the second user, the reactive social behavior may be presented without waiting for actual social behavior by the second user. 
     That is, with the image generation device  110  according to the first embodiment, if the users who are at positions spaced from each other dialogue through the avatars, it is possible to present the reactive behavior to the dialogue partner. 
     Second Embodiment 
     In the foregoing first embodiment, the description is given on the assumption that the dialogue strategy of the user  150  is determined based on the tendency of the social behavior of the user  150  to the user  140 . In contrast to this, in a second embodiment, acceptability of the social behavior of the user  150  is judged based on the tendency of the social behavior of the user  150  to the user  140  in the predetermined temporal interval, and the dialogue strategy of the user  150  is determined based on the judged acceptability. Note that the acceptability of the social behavior of the user  150  refers to a possibility that the user  150  recognizes that he or she receives the social behavior when the user  140  performs the social behavior to the user  150 . In the following, the second embodiment is described, mainly focusing on differences from the first embodiment. 
     &lt;Functional Configuration of Reactive Processing Unit of Image Generation Device&gt; 
     First, description is given of a functional configuration of the reactive processing unit  115  of the image generation device  110 .  FIG. 20  is a second diagram illustrating the functional configuration of the reactive processing unit of the image generation device. 
     The difference from  FIG. 8  is that new tables are stored in a dialogue strategy determination section  2000 , and the definition data DB  118  and the evaluation information DB  119 . Note that of the tables depicted in the definition data DB  118  and the evaluation information DB  119  in  FIG. 20 , the tables marked with a filled circle represent the new tables. 
     As illustrated in  FIG. 20 , the dialogue strategy determination section  2000  includes an action tendency identification part  2001 , an action possibility judgment part  2002 , an acceptability judgment part  2003 , and a determination part  2004 . 
     The action tendency identification part  2001  refers to the “social behavior log recording table”  1700  and analyzes the social behavior performed by the user  150  to the user  140 . The action tendency identification part  2001  also calculates a frequency of the approach tendencies (or an amount of time) and the frequency of the avoidance tendencies (or the amount of time) in the predetermined temporal interval. 
     The action tendency identification part  2001  also records the calculated frequency of the approach tendencies (or the amount of time) and frequency of the avoidance tendencies (or the amount of time) in a “temporal interval social behavior action tendency amount recording table” of the evaluation information DB  119 . 
     The action tendency identification part  2001  also refers to a “temporal interval social behavior action tendency amount threshold definition data table” stored in the definition data DB  118  and compares the calculated frequency of approach tendencies (or the amount of time) and frequency of avoidance tendencies (or the amount of time). With this, the action tendency identification part  2001  identifies any of which of the approach action tendency, the avoidance action tendency, or the intermediate action tendency the action tendency of the social behavior performed by the user  150  to the user  140  corresponds to (illustrated in  FIG. 1 ). 
     Furthermore, the action tendency identification part  2001  records the identified action tendency in the “temporal interval social behavior action tendency recording table” in the evaluation information DB  119 . 
     The action possibility judgment part  2002  judges whether or not the user  150  may take a cooperative action to the user  140  (cooperative action possibility), and records a result of the judgment in a “cooperative action possibility judgment recording table” in the evaluation information DB  119 . 
     The acceptability judgment part  2003  judges the possibility that the user  150  recognizes that he or she receives the social behavior when the user  140  performs the social behavior to the user  150 . The acceptability judgment part  2003  judges the social behavior acceptability based on the action tendency of the social behavior of the user  150  to the user  140  and the result of the judgment on the cooperative action possibility of the user  150  to the user  140 . 
     The determination part  2004  determines the dialogue strategy based on the result of the judgment on the social behavior acceptability of the user  150  and notifies the presentation control section  805  of the determined dialogue strategy. 
     Note that presentation control section  805  judges whether or not the reactive social behavior is permitted for the determined dialogue strategy. If the presentation control section  805  judges that the reactive social behavior is permitted, the presentation control section  805  transmits to the information display processing section  112  the avatar image representing the reactive social behavior of the user  150 , the reactive social behavior being associated with the determined dialogue strategy. In addition, the presentation control section  805  instructs the information display processing section  112  to display the avatar image representing the reactive social behavior of the user  150 . Furthermore, the presentation control section  805  records the dialogue strategy of this time in a “recording table of dialogue strategy determination corresponding to social behavior acceptability” in the evaluation information DB  119 . 
     &lt;Description of Table Relating to Processing of Respective Components of Reactive Processing Unit&gt; 
     In the following, description is given of the table (here, “temporal interval social behavior action tendency amount threshold definition data table” stored in the definition data DB  118 ) relating to processing of the respective components of the reactive processing unit  115  (here, the dialogue strategy determination section  2000 ). 
       FIG. 21  is a diagram illustrating an example of the temporal interval social behavior action tendency amount threshold definition data table stored in the definition data DB. As illustrated in  FIG. 21 , “temporal interval social behavior action tendency amount threshold definition data table”  2100  includes, as the information item, a “category ID”, the “action tendency”, a “threshold (ratio of frequency)”, and the “threshold (ratio of time [seconds])”. 
     The “category ID” defines the identifier for identifying the action tendency identified by the action tendency identification part  2001 . The “action tendency” defines the action tendency identified by the action tendency identification part  2001 . 
     In the “threshold (ratio of frequency)” is defined the threshold of the action tendency amount (frequency) as a condition for identifying that the action tendency is the action tendency defined in the “action tendency”. In the “threshold (ratio of time [seconds])” is defined the threshold of the action tendency amount (time) as the condition for identifying that the action tendency is the action tendency defined in the “action tendency”. 
     According to an example of  FIG. 21 , if the approach action tendency amount (frequency) is 0.55 or more, and the approach action tendency amount (time) is 0.20 or more, the action tendency identification part  2001  identifies that the social behavior targeted for processing is the approach action tendency. If the approach action tendency amount (frequency) is 0.55 or more, or the approach action tendency amount (time) is 0.20 or more, the action tendency identification part  2001  may identify that the social behavior targeted for processing is the approach action tendency. 
     According to the example of  FIG. 21 , if the avoidance action tendency amount (frequency) is 0.55 or more, and the avoidance action tendency amount (time) is 0.10 or more, the action tendency identification part  2001  identifies that the social behavior targeted for processing is the avoidance action tendency. If the avoidance action tendency amount (frequency) is 0.55 or more, or the avoidance action tendency amount (time) is 0.10 or more, the action tendency identification part  2001  may identify that the social behavior targeted for processing is the avoidance action tendency. 
     Further, according to the example of  FIG. 21 , if neither the approach action tendency nor the avoidance action tendency is identified, the action tendency identification part  2001  identifies the social behavior targeted for processing is the intermediate action tendency. Or, if the social behavior targeted for processing is both the approach action tendency and the avoidance action tendency, the action tendency identification part  2001  identifies that the social behavior targeted for processing is the intermediate action tendency. 
     &lt;Details of Presentation Control Processing of Reactive Processing Unit&gt; 
     In the following, details of the presentation control processing of the reactive processing unit  115  (illustrated in  FIG. 1 ) are described. Note that in the second embodiment, the presentation control processing of the reactive processing unit  115  is similar to the presentation control processing described with reference to  FIG. 15  in the first embodiment, and differs only in the dialogue strategy determination processing in step S 1505 . 
     Thus, here, of the presentation control processing of the reactive processing unit  115 , details of the dialogue strategy determination processing are described.  FIG. 22  is a first flowchart illustrating the details of the dialogue strategy determination processing of the reactive processing unit. 
     In step S 2201 , the action tendency identification part  2001  performs temporal interval social behavior action tendency amount calculation processing. 
     Specifically, the action tendency identification part  2001  refers to the “social behavior log recording table”  1700  (illustrated in  FIG. 17 ) in the predetermined temporal interval (between time t k-1  and time t k ). Then, the action tendency identification part  2001  discriminates the social behavior performed by the user  150  to the user  140  (or performed by the user  140  to the user  150  and illustrated in  FIG. 8 ). 
     The action tendency identification part  2001  also calculates various action tendency amounts for the discriminated social behavior, and records in the “temporal interval social behavior action tendency amount recording table” in the evaluation information DB  119 . 
     Specifically, the action tendency identification part  2001  calculates the frequency of approach tendencies (or the amount of time) and the frequency of avoidance tendencies (or the amount of time), and records in the “temporal interval social behavior action tendency amount recording table” in the evaluation information DB  119 . 
     The action tendency identification part  2001  also calculates a ratio of the frequency of approach tendencies (or the amount of time) and a ratio of the frequency of avoidance tendencies (or the amount of time), and records in the “temporal interval social behavior action tendency amount recording table” in the evaluation information DB  119 . 
       FIG. 23  is a diagram illustrating an example of the temporal interval social behavior action tendency amount recording table, stored in the evaluation information DB. A illustrated in  FIG. 23 , in the “temporal interval social behavior action tendency amount recording table”  2300  are recorded various action tendency amounts for the social behavior of the user of the avatar ID recorded in the “behaving avatar ID”. 
     The example of  FIG. 23  indicates that the “approach action tendency amount (frequency)”, the “avoidance action tendency amount (frequency)”, the “approach action tendency amount (time [seconds])”, and the “avoidance action tendency amount (time [seconds])” are recorded as the action tendency amount. The example of  FIG. 23  also indicates that the “approach action tendency amount (ratio of frequency)”, the “avoidance action tendency amount (ratio of frequency)”, the “approach action tendency amount (ratio of time [seconds])”, and the “avoidance action tendency amount (ratio of time [seconds])” are further recorded as the action tendency amount. 
     Turning back to  FIG. 22 , in step S 2202 , the action tendency identification part  2001  performs temporal interval social behavior action tendency identification processing. 
     Specifically, the action tendency identification part  2001  compares the calculated approach action tendency amount and avoidance action tendency amount with the “temporal interval social behavior action tendency amount threshold definition data table”  2100 . With this, the action tendency identification part  2001  identifies the action tendency of the social behavior of the user of the avatar ID recorded in the “behaving avatar ID”, the social behavior being performed on the user of the avatar ID recorded in the “behaved avatar ID”. In the present embodiment, the action tendency identification part  2001  identifies any of the approach action tendency, the avoidance action tendency, or the intermediate action tendency. 
     The action tendency identification part  2001  also records the result of the identification of the action tendency in the “temporal interval social behavior action tendency recording table” in the evaluation information DB  119 . 
       FIG. 24  is a diagram illustrating an example of the temporal interval social behavior action tendency recording table, recorded in the evaluation information DB. As illustrated in  FIG. 24 , in the “temporal interval social behavior action tendency recording table”  2400  are included the “behaving avatar ID” and the “behaved avatar ID” and are recorded the avatar ID of the user who performs the social behavior and the avatar ID of the user who receives the social behavior. In addition, in the “temporal interval social behavior action tendency recording table”  2400  is included the “social behavior action tendency” and are recorded the result of the identification of the action tendency identified by the action tendency identification part  2001 . 
     Turning back to  FIG. 22 , in step S 2203 , the action possibility judgment part  2002  performs cooperative action possibility judgment processing. 
     Specifically, the action possibility judgment part  2002  refers to the “social behavior action tendency” in the predetermined temporal interval (between time t k-1  and time t k ) in the “temporal interval social behavior action tendency recording table”  2400 . With this, the action possibility judgment part  2002  discriminates the action tendency of the social behavior performed by the user of the avatar ID recorded in the “behaving avatar ID” to the user of the avatar ID recorded in the “behaved avatar ID”. 
     The action possibility judgment part  2002  also discriminates attribute information of the user of the avatar ID recorded in the “behaved avatar ID”. The attribute information of the user of the avatar ID recorded in the “behaved avatar ID” includes age, gender, or the like of the user. 
     The action possibility judgment part  2002  also discriminates time elapsed after the user of the avatar ID recorded in the “behaving avatar ID” and the user of the avatar ID recorded in the “behaved avatar ID” dialogue for the first time. 
     Furthermore, based on the discrimination result (action tendency, attribute information, elapsed time, or the like), the action possibility judgment part  2002  judges the possibility that the user of the avatar ID recorded in the “behaved avatar ID” takes the cooperative action to the user of the avatar ID recorded in the “behaving avatar ID”. The action possibility judgment part  2002  records the judgment result on the cooperative action possibility in the “cooperative action possibility judgment recording table” in the evaluation information DB  119 . 
       FIG. 25  is a diagram illustrating an example of the cooperative action possibility judgment recording table recorded in the evaluation information DB. As illustrated in  FIG. 25 , the “cooperative action possibility judgment recording table”  2500  includes the “behaving avatar ID”, the “behaved avatar ID”, and the “cooperative action possibility”. In the “cooperative action possibility judgment recording table”  2500  is recorded the judgment result of the possibility that the user of the avatar ID recorded in the “behaving avatar ID” takes the cooperative action to the user of the avatar ID recorded in the “behaved avatar ID”. 
     The cooperative action possibility being “High” indicates that the action possibility judgment part  2002  judges that the possibility of taking the cooperative action is high. On the other hand, the cooperative action possibility being “Low” indicates that it is judged that the possibility of taking the cooperative action is not possible. 
     For example, if the user who receives the social behavior continues to perform the social behavior of the avoidance action tendency for 5 minutes or longer, the action possibility judgment part  2002  judges that the possibility of taking the cooperative action is low and records “Low”. 
     In addition, for example, if the user who receives the social behavior is under primary school age, the action possibility judgment part  2002  judges that the possibility of the user taking the cooperative action is low, and records “Low”. 
     Furthermore, for example, if the elapsed time after the user who receives the social behavior first dialogues with the user who performs the social behavior is within 10 minutes, the action possibility judgment part  2002  judges that the possibility of taking the cooperative action is low, and records “Low”. 
     Note that the example on the first data row of  FIG. 25  indicates that it is judged that the possibility of the user  140  with the avatar ID=“AV 1 ” taking the cooperative action to the user  150  with the avatar ID=“AV 2 ” is high (each illustrated in  FIG. 1 ). 
     In addition, the example on the second data row of  FIG. 25  indicates that it is judged that the possibility of the user  150  with the avatar ID=“AV 2 ” taking the cooperative action to the user  140  with the avatar ID=“AV 1 ” is high. 
     Turning back to  FIG. 22 , in step S 2204 , the acceptability judgment part  2003  performs social behavior acceptability judgment processing. 
     Specifically, the acceptability judgment part  2003  refers to the “social behavior action tendency” in the predetermined temporal interval (between time t k-1  and time t k ) in the “temporal interval social behavior action tendency recording table”  2400 . With this, the acceptability judgment part  2003  discriminates the judgment result of the possibility of the user of the avatar ID recorded in the “behaving avatar ID” performing the cooperative action to the user of the avatar ID recorded in the “behaved avatar ID”. 
     In addition, the acceptability judgment part  2003  refers to the “cooperative action possibility” in the predetermined temporal interval (between time t k-1  and time t k ) in the “cooperative action possibility judgment recording table”  2500 . With this, the acceptability judgment part  2003  discriminates the judgment result on the possibility of the user of the avatar ID recorded in the “behaving avatar ID” taking the cooperative action to the user of the avatar ID recorded in the “behaved avatar ID”. 
     The acceptability judgment part  2003  judges the social behavior acceptability at time t k  based on the discriminated action tendency and the judgment result of the discriminated cooperative action possibility. That is, the acceptability judgment part  2003  judges the possibility of the discrimination that the user of the avatar ID recorded in the “behaved avatar ID” receives the social behavior from the user of the avatar ID recorded in the “behaving avatar ID”. 
     The acceptability judgment part  2003  judges the possibility of discriminating that the social behavior is received, by judging whether both of the following conditions are satisfied:—The discriminated action tendency is the approach action tendency or the intermediate action tendency, —The judgment result of the cooperative action possibility is High. 
     If the above conditions are satisfied, the acceptability judgment part  2003  judges that the possibility of discriminating that to the user of the avatar ID recorded in the “behaved avatar ID”, the user of the avatar ID recorded in the “behaving avatar ID” receives the social behavior is high. That is, the acceptability judgment part  2003  judges “Acceptable”. 
     On the other hand, if either of the above conditions is not satisfied or if both of the above conditions are not satisfied, the acceptability judgment part  2003  judges that the possibility of discriminating that to the user of the avatar ID recorded in the “behaved avatar ID”, the social behavior is received is low. That is, the acceptability judgment part  2003  judges “Not Acceptable”. 
     Furthermore, the acceptability judgment part  2003  records the result of the social behavior acceptability judgment processing in the “social behavior acceptability judgment recording table” in the evaluation information DB  119 . 
       FIG. 26  is a diagram illustrating an example of the social behavior acceptability judgment recording table recorded in the evaluation information DB. As illustrated in  FIG. 26 , a “social behavior acceptability judgment recording table”  2600  includes the “behaving avatar ID” and the “behaved avatar ID” and records the respective avatar IDs. 
     In addition, the “social behavior acceptability judgment recording table”  2600  includes the “social behavior acceptability”. In the “social behavior acceptability” is recorded the acceptability of the social behavior of the user of the avatar ID recorded in the “behaving avatar ID” to the user of the avatar ID recorded in the “behaved avatar ID”. 
     An example on the first data row of  FIG. 26  indicates that the possibility of discriminating that to the user  150  with the avatar ID=“AV 2 ”, the user  140  with the avatar ID=“AV 1 ” receives the social behavior is high (“Acceptable”) (each illustrated in  FIG. 1 ). This is because the action tendency of the social behavior performed by the user  140  to the user  150  is the intermediate action tendency and the cooperative action possibility of the user  150  is “High”. 
     On the other hand, the example on the second data row of  FIG. 26  indicates that the possibility of discriminating that to the user  140 , the user  150  receives the social behavior is low (“Not Acceptable”). This is because the action tendency of the social behavior performed by the user  150  to the user  140  is the avoidance action tendency. 
     Turning back to  FIG. 22 , in step S 2205 , the determination part  2004  performs the dialogue strategy determination processing based on the social behavior acceptability judgment. 
     The determination part  2004  refers to the “social behavior acceptability judgment recording table”  2600 . Then, the determination part  2004  determines the dialogue strategy o the user of the avatar ID recorded in the “behaved avatar ID”, based on the judgment result of the social behavior acceptability recorded in the “social behavior acceptability”. 
     For example, in the case of the first row of the data rows of the “social behavior acceptability judgment recording table”  2600 , the social behavior acceptability is “Acceptable”. When the social behavior acceptability to the user  150  of the behaved avatar ID=“AV 2 ” viewed from the user  140  of the behaving avatar ID=“AV 1 ” is judged, the determination part  2004  determines the dialogue strategy (“positive” strategy). 
     In addition, in the case of the second row of the data rows of the “social behavior acceptability judgment recording table”  2600 , the social behavior acceptability is “Not Acceptable”. When the social behavior acceptability to the user  140  of the behaved avatar ID=“AV 1 ” viewed from the user  150  of the behaving avatar ID=“AV 2 ” is judged, the determination part  2004  determines the dialogue strategy (“negative” strategy). 
     Note that the method of determining the dialogue strategy by the determination part  2004  is not limited thereto, and the dialogue strategy may be determined by combining the “social behavior action tendency”, the “cooperative action possibility”, and the “social behavior acceptability”. 
     For example, if—the “social behavior acceptability”=“Acceptable”, —the “social behavior action tendency”=the “approach action tendency” or the “intermediate action tendency”, and—the “cooperative action possibility”=“Low”, the dialogue strategy may be determined to be “Dynamically_positive”. 
     Alternatively, if—the “social behavior acceptability”=“Acceptable”, —the “social behavior action tendency”=the “avoidance action tendency”, and—the “cooperative action possibility”=“Low”, the dialogue strategy may be determined to be “Minimally_positive”. 
     Alternatively, if—the “social behavior acceptability”=“Not Acceptable”, —the “social behavior action tendency”=the “avoidance action tendency”, and—the “cooperative action possibility”=“High”, the dialogue strategy may be determined to be “Shortly_negative”. 
     Note that the dialogue strategy determined by the determination part  2004  is recorded in the “recording table of dialogue strategy determination corresponding to social behavior acceptability” in the evaluation information DB  119  by the presentation control section  805 .  FIG. 27  is a diagram illustrating an example of the recording table of dialogue strategy determination corresponding to social behavior acceptability, recorded in the evaluation information DB. 
     As illustrated in  FIG. 27 , the “recording table of dialogue strategy determination corresponding to social behavior acceptability”  2700  includes the “behaving avatar ID” and the “behaved avatar ID”, as the information item. Then, the avatar ID of the user is recorded in these information items. In addition, the“recording table of dialogue strategy determination corresponding to social behavior acceptability”  2700  also includes the “dialogue strategy”, as the information item. In the “dialogue strategy” is recorded the dialogue strategy that is the dialogue strategy by the user with the avatar ID recorded in the “behaving avatar ID” to the user with the avatar ID recorded in the “behaved avatar ID”, and that is determined by the determination part  2004 . 
     According to the example on the first data row of  FIG. 27 , the “positive” strategy is determined as the dialogue strategy of the user  140  to the user  150  when the user  150  performs the social behavior to the user  140  (each illustrated in  FIG. 1 ). 
     In addition, according to the example on the second data row of  FIG. 27 , the “shortly_positive” strategy is determined as the dialogue strategy of the user  150  to the user  140  when the user  140  performs the social behavior to the user  150 . 
     As is clear from the foregoing description, in determining the dialogue strategy based on the social behavior tendency, the image generation device  110  in the second embodiment—quantifies the social behavior tendency based on the frequency or time in the predetermined temporal interval, and—identifies the action tendency through the comparison with the threshold. The image generation device  110 —judges the social behavior acceptability based on the action tendency and the cooperative action possibility. The image generation device  110 —determines the dialogue strategy based on the judgment result of the social behavior acceptability. 
     With this, according to the image generation device  110  of the second embodiment, the reactive behavior based on the dialogue strategy determined from the standpoint of the social behavior acceptability may be presented to the dialogue partner. 
     Third Embodiment 
     In the foregoing second embodiment, the case where the dialogue strategy is determined through judgment of the social behavior acceptability. In contrast to this, in a third embodiment, the dialogue strategy is determined to further judge relationship level with the dialogue partner and adjust the relationship level. Note that the relationship level is information representing level of friendliness to the dialogue partner. In the following, the third embodiment is described, mainly focusing on differences from the foregoing second embodiment. 
     &lt;Functional Configuration of Reactive Processing Unit of Image Generation Device&gt; 
     First, description is given of the functional configuration of the reactive processing unit  115  of the image generation device  110  in the third embodiment with reference to  FIG. 28 .  FIG. 28  is a third diagram illustrating the functional configuration of the reactive processing unit of the image generation device. 
     The difference from  FIG. 20  is that new tables are stored in a dialogue strategy determination section  2800 , and the definition data DB  118  and the evaluation information DB  119 . Note that of the tables depicted in the definition data DB  118  and the evaluation information DB  119  in  FIG. 28 , the tables marked with a filled circle represent the new tables. 
     As illustrated in  FIG. 28 , the dialogue strategy determination section  2800  includes the action tendency identification part  2001 , the action possibility judgment part  2002 , the acceptability judgment part  2003 , a relationship level processing part  2801 , a relatedness level processing part  2802 , a relationship adjustment part  2803 , and a determination part  2804 . Here, the term “relationship” is from a view point of a behaving person, while the term “relatedness” is from a view point of a behaved person, namely a person receiving the behavior from the behaving person. 
     The relationship level processing part  2801  calculates an amount of information (information disclosure amount) included in the speech or the social behavior performed by the user  150  to the user  140  (illustrated in  FIG. 1 ), triggered by the user  150  performing the speech or the social behavior. Note that the relationship level processing part  2801  refers to the “social behavior value calculation recording table” and a “speech value calculation recording table” in calculating the information disclosure amount. The relationship level processing part  2801  also records the calculated information disclosure amount in a “recording table of information disclosure amount to dialogue partner”. 
     The relationship level processing part  2801  also judges the relationship level considering the user  150  appropriate to the user  140 , based on the calculated information disclosure amount, and records the judgment result in the “judgment recording table of relationship level considered appropriate to dialogue partner”. 
     Furthermore, the relationship level processing part  2801  calculates a relationship progress degree between the judged relationship level and a relationship level that is a next goal of the relationship progress, and records in a “relationship progress degree recording table”. Note that although in the present embodiment, description is given of a case where the relationship level is judged based on the information disclosure amount, a method of judging the relationship level is not limited thereto, and the relationship level processing part  2801  may judge the relationship level with any other judgment method. 
     The relatedness level processing part  2802  calculates the amount of information (information disclosed amount) included in the speech or the social behavior that the user  150  receives from the user  140 , triggered by recording of the speech or the social behavior from the user  140 . The relatedness level processing part  2802  records the calculated information disclosed amount in the “recording table of information disclosed amount from dialogue partner”. 
     The relatedness level processing part  2802  also estimates a relatedness level considering the user  140  appropriate for the user  150 , based on the calculated information disclosed amount. The relatedness level processing part  2802  records the estimated relatedness level in a “relatedness level estimation recording table considering dialogue partner appropriate based on information disclosed amount from dialogue partner”. 
     If the acceptability judgment part  2003  judges that the social behavior acceptability is “Acceptable”, the relationship adjustment part  2803  controls a direction of adjustment of the relationship level. Specifically, the relationship adjustment part  2803  compares the relationship level to the dialogue partner calculated for the user  150  with the relatedness level from the dialogue partner, and controls the direction of the adjustment of the relationship level of the user  150  to the user  140 , based on a magnitude relationship of the relationship level to the dialogue partner calculated for the user  150  and the relatedness level from the dialogue partner. 
     The determination part  2804  refers to a “dialogue strategy definition data table by relationship level” stored in the definition data DB  118  and determines the dialogue strategy of the user  150  to the user  140  according to the direction of the adjustment of the relationship level. 
     Note that the presentation control section  805  judges whether or not the reactive social behavior is permitted, for the determined dialogue strategy. If the presentation control section  805  judges that the reactive social behavior is permitted, the presentation control section  805  also transmits to the information display processing section  112  the avatar image representing the reactive social behavior of the user  150 , being associated with the determined dialogue strategy. The presentation control section  805  instructs the information display processing section  112  to display the avatar image representing the reactive social behavior of the user  150 . Furthermore, the presentation control section  805  records the dialogue strategy of this time in a “recording table of dialogue strategy determination corresponding to relationship level” in the evaluation information DB 119 . 
     &lt;Description of Table Relating to Processing of Respective Components of Reactive Processing Unit&gt; 
     In the following, description is given of the tables (here, the “dialogue strategy definition data table by relationship level” stored in the definition data DB  118 ) including the data relating to the processing of the respective components (here, the dialogue strategy determination section  2800 ) of the reactive processing unit  115 . 
       FIG. 29  is a diagram illustrating an example of the dialogue strategy definition data table by relationship level, stored in the definition data DB. As illustrated in  FIG. 29 , the “dialogue strategy definition data table by relationship level”  2900  includes, as the information item, the “relationship level”, a “distance from a default strategy”, and the “dialogue strategy”. 
     The “relationship level” defines the relationship level of other user viewed from one user. An example of  FIG. 29  indicates that the relationship level is divided into three stages. Of these stages, “0_superficial” indicates that the relationship of the other user viewed from the one user is at a superficial level. “1_intimate” indicates that the relationship of the other user viewed from the one user is at an intimate level. “2—personal” indicates that the relationship of the other user viewed from the one user is at more intimate level. 
     The “distance from a default strategy” defines the distance from the default strategy at each relationship level. 
     The “dialogue strategy” defines the dialogue strategy according to a distance from a default dialogue strategy at each relationship level. 
     According to  FIG. 29 , if the relationship level is “0_superficial”, the default dialogue strategy (that is, the dialogue strategy a “distance from the default strategy” of which is 0) is a “Shortly_positive” strategy. In addition, the dialogue strategy in a positive direction to the default dialogue strategy is a “Sunnily_positive” strategy or a “Sunnily_Shortly_positive” strategy. Furthermore, the dialogue strategy in a negative direction to the default dialogue strategy is a “Minimally_positive” strategy or a “Minimally_Shortly_positive” strategy. 
     Similarly, the “dialogue strategy definition data table by relationship level”  2900  defines, for a case of the relationship level of “1_intimate”, the default dialogue strategy, the dialogue strategy in the positive direction to the default dialogue strategy, and the dialogue strategy in the negative direction. 
     Similarly, the “dialogue strategy definition data table by relationship level”  2900  defines, for a case of the relationship level of “2_personal”, the default dialogue strategy, the dialogue strategy in the positive direction to the default dialogue strategy, and the dialogue strategy in the negative direction. 
     &lt;Details of Presentation Control Processing of Reactive Processing Unit&gt; 
     In the following, details of the presentation control processing of the reactive processing unit  115  are described. Note that in the third embodiment, the presentation control processing of the reactive processing unit  115  is similar to the presentation control processing described with reference to  FIG. 15  in the first embodiment, and differs only in the dialogue strategy determination processing in step S 1505 . 
     Thus, here, of the presentation control processing of the reactive processing unit  115 , details of the dialogue strategy determination processing are described.  FIG. 30  is a second flowchart illustrating the details of the dialogue strategy determination processing of the reactive processing unit. 
     As illustrated in  FIG. 30 , the dialogue strategy determination processing of the reactive processing unit  115  (illustrated in  FIG. 1 ) in the third embodiment has a process from steps S 3001  to S 3004 , in addition to the process of steps s 2201  to S 2204  described in the second embodiment. 
     Step S 3001  is relationship level processing by the relationship level processing part  2801 , and step S 3002  is relatedness level processing by the relatedness level processing part  2802 . In step S 3003  is relationship adjustment control processing by the relationship adjustment part  2803 , and step S 3004  is the dialogue strategy determination processing based on the relationship adjustment control by the determination part  2804 . In the following, details of the respective processes from steps S 3001  to S 3004  are described. 
     Note that in the respective processes from steps S 3001  to S 3004 , the various information relating to the social behavior (various information relating to the non-verbal action) as well as the various information relating to the speech (various information relating to the verbal-action) are used. Thus, here, first, description is given of the speech value calculation recording table in which the various information relating to the speech is recorded. 
       FIG. 31  is a diagram illustrating an example of the speech value calculation recording table recorded in the evaluation information DB. As described above, the various information relating to the social behavior (various information relating to the non-verbal action) is calculated or identified by the social behavior value calculation section  802  (illustrated in  FIG. 8 ) and recorded in the “social behavior value calculation recording table”  1800  (illustrated in  FIG. 18 ). 
     On the other hand, the various information relating to the speech (various information relating to the verbal action) is calculated by a speech value calculation section (not illustrated) and recorded in the “speech value calculation recording table”  3100 . 
     As illustrated in  FIG. 31 , the “speech value calculation recording table”  3100  includes, as the information item, the “DB recording time”, the “recording start time”, the “recording end time”, the “behaving avatar ID”, and the “behaved avatar ID”. The “speech value calculation recording table”  3100  also includes, as the information item, a “spoken voice”, a “received voice”, a “spoken text”, a “received text”, a “information disclosure frequency based on personal information”, and “information disclosure frequency based on general topic”. Furthermore, the “speech value calculation recording table”  3100  includes, as the information item, “information disclosed frequency based on personal information” and “information disclosed frequency based on general topic”. 
     Among these, as the respective information items from the “DB recording time” to the “behaved avatar ID” when the various information items are viewed from the left-to-right direction in  FIG. 31  are similar to the information items included in the “social behavior value calculation recording table”  1800 , description is omitted here. 
     In the “spoken voice” is recorded a name of a file to which data of voice spoken by the user of the avatar ID recorded in the “behaving avatar ID” is stored. 
     In the “received voice” is recorded the name of the file to which data of voice received by the user of the avatar ID recorded in the “behaved avatar ID” is stored. 
     In the “spoken text” is recorded text data of the file the stored file name of which is recorded in the “spoken voice”. 
     In the “received text” is recorded the text data of the file the stored file name of which is recorded in the “received voice”. 
     In the “information disclosure frequency based on personal information” is recorded a frequency of the user of the avatar ID recorded in the “behaving avatar ID” disclosing personal information by the speech. In the “information disclosure frequency based on general topic” is recorded the frequency of the user of the avatar ID recorded in the “behaving avatar ID” disclosing a general topic by the speech. 
     In the “information disclosed frequency based on personal information” is recorded a frequency of the user of the avatar ID recorded in the “behaved avatar ID” receiving the personal information disclosure by receiving voice. In the “information disclosed frequency based on general topic” is recorded the frequency of the user of the avatar ID recorded in the “behaving avatar ID” receiving the general topic disclosure by receiving the voice. 
     (1) Details of the Relationship Level Processing (Step S 3001 ) 
       FIG. 32  is a flowchart illustrating details of the relationship level processing. The relationship level processing part  2801  (illustrated in  FIG. 28 ) performs the relationship level processing for each of the data rows of the “social behavior value calculation recording table”  1800  (illustrated in  FIG. 18 ) and the “speech value calculation recording table”  3100  (illustrated in  FIG. 31 ). 
     In step S 3201 , the relationship level processing part  2801  judges whether or not there is any unprocessed data row, for the “social behavior value calculation recording table”  1800  and the “speech value calculation recording table”  3100 . In step S 3201 , if the relationship level processing part  2801  judges that there is any unprocessed data row, the processing proceeds to step S 3202 . 
     In step S 3202 , the relationship level processing part  2801  calculates an information disclosure score based on the non-verbal action. 
     Specifically, the relationship level processing part  2801  refers to the “social behavior value calculation recording table”  1800 , and extracts the unprocessed data row. The relationship level processing part  2801  extracts, as the unprocessed data row, the data row that is the data row of the user  150  (behaving avatar ID=“AV 2 ”) and that is recorded after the time recorded in the “recording end time” of the last processed data row. 
     The relationship level processing part  2801  also extracts, from the extracted unprocessed data row, the information recorded in “information disclosure by non-verbal action (whether or not there is touch on body)” and the information recorded in “information disclosure by non-verbal action (whether or not intention and demeanor (expression or the like) are presented”. Furthermore, the relationship level processing part  2801  calculates the information disclosure score by the non-verbal action, based on the extracted information. 
     For example, on the extracted unprocessed data row, if the information recorded in the “information disclosure by non-verbal action (whether or not there is touch on body)” is “Yes”, the relationship level processing part  2801  adds 5 points to the information disclosure score by the non-verbal action. Similarly, if the information recorded in the “information disclosure by non-verbal action (whether or not intention and demeanor (expression or the like) are presented” is “Yes”, the relationship level processing part  2801  adds 5 points to the information disclosure score by the non-verbal action. 
     In step S 3203 , the relationship level processing part  2801  calculates the information disclosure score by the verbal-action. 
     Specifically, the relationship level processing part  2801  refers to the “speech value calculation recording table”  3100 , and extracts the unprocessed data row. The relationship level processing part  2801  extracts, as the unprocessed data row, the data row that is the data row of the user  150  (behaving avatar ID=“AV 2 ” and that is recorded after the time recorded in the “recording end time” of the last processed data row. 
     The relationship level processing part  2801  also extracts, from the extracted unprocessed data row, the information recorded in the “information disclosure frequency based on personal information” and the information recorded in “information disclosure frequency based on general topic”, and calculates the information disclosure score. 
     For example, on the extracted unprocessed data row, if the information recorded in the “information disclosure frequency based on personal information” is “1”, the relationship level processing part  2801  adds 5 points to the information disclosure score by the verbal-action. Similarly, if the information recorded in the “information disclosure frequency based on general topic” is “1”, the relationship level processing part  2801  adds 1 point to the information disclosure score by the verbal-action. 
     In step S 3204 , the relationship level processing part  2801  calculates the information disclosure amount to the dialogue partner, and records in the “information disclosure amount recording table”. 
     Specifically, the relationship level processing part  2801  calculates the information disclosure amount based on the information disclosure score by the non-verbal action and the information disclosure score by the verbal-action. Note that the relationship level processing part  2801  may simply add the information disclosure score by the non-verbal action and the information disclosure score by the verbal-action to calculate the information disclosure amount or may calculate the information disclosure amount by weighting and adding. 
     The relationship level processing part  2801  records the calculated information disclosure amount together with the information disclosure score by the non-verbal action and the information disclosure score by the verbal-action, in the “recording table of information disclosure amount to dialogue partner” in the evaluation information dB  119 . 
       FIG. 33  is a diagram illustrating an example of a recording table of information disclosure amount to dialogue partner recorded in the evaluation information DB. As illustrated in  FIG. 33 , the “recording table of information disclosure amount to dialogue partner”  3300  includes the “behaving avatar ID” and the “behaved avatar ID”. In the “behaving avatar ID” and the “behaved avatar ID”, the avatar ID of the user who performs the verbal-action/non-verbal action and the avatar ID of the user wo receives the social behavior as a result of the user performing the verbal-action/non-verbal action are recorded. 
     In addition, the “recording table of information disclosure amount to dialogue partner”  3300  includes, as the information item, the “information disclosure score by the non-verbal action” and the “information disclosure score by the verbal action”. Then, in the respective information items are recorded the information disclosure score by the non-verbal action and the information disclosure score by the verbal-action calculated by the relationship level processing part  2801  (illustrated in  FIG. 28 ). 
     Furthermore, in the “recording table of information disclosure amount to dialogue partner”  3300  is included the “information disclosure amount” as the information item and is recorded the information disclosure amount calculated by the relationship level processing part  2801 . Note that the example of  FIG. 33  indicates the case where the information disclosure amount is calculated by simply adding the information disclosure score by the non-verbal action and the information disclosure score by the verbal-action. 
     Turning back to  FIG. 32 , in step S 3205 , the relationship level processing part  2801  performs processing to judge the relationship level to the dialogue partner. 
     Specifically, the relationship level processing part  2801  refers to the “judgment recording table of relationship level considered appropriate to dialogue partner”, and extracts the latest value recorded in “cumulative information disclosure amount”. Note that  FIG. 34  is a diagram illustrating an example of the judgment recording table of relationship level considered appropriate to dialogue partner, recorded in the evaluation information DB. 
     The relationship level processing part  2801  also extracts the latest value recorded in the “information disclosure amount” in “recording table of information disclosure amount to dialogue partner”  3300 . 
     Then, the relationship level processing part  2801  newly calculates cumulative information disclosure amount based on the latest value recorded in the “cumulative information disclosure amount” and the latest value recorded in the “information disclosure amount”. 
     The relationship level processing part  2801  also judges whether or not the newly calculated cumulative information disclosure amount exceeds a predetermined threshold. 
     If the relationship level processing part  2801  judges that the newly calculated cumulative information disclosure amount exceeds the predetermined threshold, the relationship level processing part  2801  refers to the “judgment recording table of relationship level considered appropriate to dialogue partner”  3400 . The relationship level processing part  2801  extracts the latest relationship level recorded in the “relationship level considered appropriate to dialogue partner”. The relationship level processing part  2801  also moves the extracted relationship level to the next relationship level. 
     Moving to the next relationship level refers to changing the extracted relationship level to “1_intimate” if the extracted relationship level is “0_superficial”. Alternatively, moving to the next relationship level refers to changing the extracted relationship level to “2_personal” if the extracted relationship level is “1_intimate”. 
     The relationship level processing part  2801  associates the extracted relationship level of the next relationship level with the newly calculated cumulative information disclosure amount, and records in the “judgment recording table of relationship level considered appropriate to dialogue partner”  3400 . Note that the relationship level processing part  2801  resets the cumulative information disclosure amount to 0, if the relationship level processing part  2801  records the next relationship level. 
     In step S 3206 , the relationship level processing part  2801  performs processing to calculate relationship level progress to the dialogue partner. 
     Specifically, the relationship level processing part  2801  refers to the “judgment recording table of relationship level considered appropriate to dialogue partner”  3400 , and extracts the value newly recorded in the “cumulative information disclosure amount”. The relationship level processing part  2801  also extracts a threshold used to calculate the “relationship level considered appropriate to dialogue partner” in the “judgment recording table of relationship level considered appropriate to dialogue partner”  3400 . 
     Furthermore, the relationship level processing part  2801  calculates the relationship progress degree based on the extracted “cumulative information disclosure amount” and the extracted threshold. The relationship progress degree is an indicator of how much the cumulative information disclosure amount increases at each relationship level (0_superficial, 1_intimate, and 2_personal). As described above, the cumulative information amount increases to the predetermined threshold for moving to the next relationship level, and is reset when exceeding the predetermined threshold. Thus, the relationship progress degree is calculated based on a ratio of the newly calculated cumulative information disclosure amount to the threshold for moving to the next relationship level. 
     The relationship level processing part  2801  records the relationship progress degree in the “relationship progress degree recording table” in the evaluation information DB  119 . 
       FIG. 35  is a diagram illustrating an example of a relationship progress degree recording table, recorded in the evaluation information DB. As illustrated in  FIG. 35 , the “relationship progress degree recording table”  3500  includes, as the information item, the “relationship level considered appropriate to dialogue partner” and “relationship progress degree”. In the respective information items is recorded the calculation result calculated in the relationship level processing part  2801  (illustrated in  FIG. 28 ). 
     (2) Details of the Relatedness Level Processing (Step S 3002 ) 
       FIG. 36  is a flowchart illustrating details of relatedness level processing. The relatedness level processing part  2802  (illustrated in  FIG. 28 ) performs the relationship level processing on the respective data rows of the “social behavior value calculation recording table”  1800  (illustrated in  FIG. 18 ) and the “speech value calculation recording table”  3100  (illustrated in  FIG. 31 ). 
     In step S 3601 , the relatedness level processing part  2802  judges whether or not there is any unprocessed data row for the “social behavior value calculation recording table”  1800  and the “speech value calculation recording table”  3100 . In step S 3601 , if the relatedness level processing part  2802  judges that there is the unprocessed data row, the processing proceeds to step S 3602 . 
     In step S 3602 , the relatedness level processing part  2802  calculates an information disclosed score by the non-verbal action. 
     Specifically, the relatedness level processing part  2802  refers to the “social behavior value calculation recording table”  1800 , and extracts the unprocessed data row. The relatedness level processing part  2802  extracts, as the unprocessed data row, the data row that is the data row of the user  140  (behaving avatar ID=“AV 1 ”) and that is recorded after the time recorded in the “recording end time” of the last processed data row. 
     The relatedness level processing part  2802  also extracts, from the extracted unprocessed data row, the information recorded in “information disclosed by non-verbal action (whether or not there is touch on body)” and the information recorded in “information disclosed by non-verbal action (whether or not intention and demeanor (expression or the like) are presented”. Furthermore, the relatedness level processing part  2802  calculates the information disclosed score by the non-verbal action, based on the extracted information. 
     For example, on the extracted unprocessed data row, if the information recorded in the “information disclosed by non-verbal action (whether or not there is touch on body)” is “Yes”, the relatedness level processing part  2802  adds 5 points to the information disclosed score by the non-verbal action. Similarly, if the information recorded in the “information disclosed by non-verbal action (whether or not intention and demeanor (expression or the like) are presented” is “Yes”, the relatedness level processing part  2802  adds 5 points to the information disclosed score by the non-verbal action. 
     In step S 3603 , the relatedness level processing part  2802  calculates the information disclosed score by the verbal-action. 
     Specifically, the relatedness level processing part  2802  refers to the “speech value calculation recording table”  3100 , and extracts the unprocessed data row. The relatedness level processing part  2802  extracts, as the unprocessed data row, the data row that is the data row of the user  140  (behaving avatar ID=“AV 1 ” and that is recorded after the time recorded in the “recording end time” of the last processed data row. 
     The relatedness level processing part  2802  also extracts, from the extracted unprocessed data row, the information recorded in the “information disclosed frequency based on personal information” and the information recorded in “information disclosed frequency based on general topic”. Furthermore, the relatedness level processing part  2802  calculates the information disclosed score based on the extracted information. 
     For example, on the extracted unprocessed data row, if the information recorded in the “information disclosed frequency based on personal information” is “1”, the relatedness level processing part  2802  adds 5 points to the information disclosed score by the verbal-action. Similarly, if the information recorded in the “information disclosed frequency based on general topic” is “1”, the relatedness level processing part  2802  adds 1 point to the information disclosed score by the verbal-action. 
     In step S 3604 , the relatedness level processing part  2802  calculates the information disclosed amount to the dialogue partner. 
     Specifically, based on the information disclosed score by the non-verbal action and the information disclosed score by the verbal-action, the relatedness level processing part  2802  calculates the information disclosed amount, which is the information disclosure amount of the information received by the user  150  from the user  140  (illustrated in  FIG. 1 ). Note that the relatedness level processing part  2802  may simply add the information disclosed score by the non-verbal action and the information disclosed score by the verbal-action to calculate the information disclosed amount or may calculate the information disclosed amount by weighting and adding. 
     Furthermore, the relatedness level processing part  2802  records the calculated information disclosed amount together with the information disclosed score by the non-verbal action and the information disclosed score by the verbal-action, in the “recording table of information disclosed amount from dialogue partner” in the evaluation information dB  119 . 
       FIG. 37  is a diagram illustrating an example of a recording table of information disclosed amount from dialogue partner recorded in the evaluation information DB. As illustrated in  FIG. 37 , the “recording table of information disclosed amount from dialogue partner”  3700  includes the “behaving avatar ID” and the “behaved avatar ID”, as the information item. In these information items are recorded the avatar ID of the user who performs the social behavior and the avatar ID of the user who receives the social behavior. 
     In addition, the “recording table of information disclosed amount from dialogue partner”  3700  includes, as the information item, the “information disclosed score by the non-verbal action” and the “information disclosed score by the verbal action”. In these information items are recorded the information disclosed score by the non-verbal action and the information disclosed score by the verbal-action calculated by the relatedness level processing part  2802  (illustrated in  FIG. 28 ). 
     Furthermore, in the “recording table of information disclosed amount from dialogue partner”  3700  is included the “information disclosed amount” as the information item and is recorded the information disclosed amount calculated by the relatedness level processing part  2802 . Note that the example of  FIG. 37  indicates the case where the information disclosed amount is calculated by simply adding the information disclosed score by the non-verbal action and the information disclosed score by the verbal-action. 
     Subsequently, in step S 3605  in  FIG. 36 , the relatedness level processing part  2802  performs estimation processing of relatedness level from dialogue partner. 
     Specifically, the relatedness level processing part  2802  refers to the “relatedness level estimation recording table considering dialogue partner appropriate, based on information disclosed amount from dialogue partner” in the evaluation information DB  119 , and extracts the latest value recorded in “cumulative information disclosed amount”. Note that  FIG. 38  is a diagram illustrating an example of the relatedness level estimation recording table considering dialogue partner appropriate based on information disclosed amount from dialogue partner, recorded in the evaluation information DB. 
     The relatedness level processing part  2802  refers to the “recording table of information disclosed amount from dialogue partner”  3700  (illustrated in  FIG. 37 ), and extracts the latest value recorded in the “information disclosed amount”. 
     Then, the relatedness level processing part  2802  newly calculates the cumulative information disclosed amount based on the latest value recorded in the “cumulative information disclosed amount” and the latest value recorded in the “information disclosed amount”. 
     The relatedness level processing part  2802  also judges whether or not the newly calculated cumulative information disclosed amount exceeds the predetermined threshold. 
     If the relatedness level processing part  2802  judges that the newly calculated cumulative information disclosed amount exceeds the predetermined threshold, the relatedness level processing part  2802  refers to a “relatedness level estimation recording table considering dialogue partner appropriate, based on information disclosed amount from dialogue partner”  3800 . Then, the relatedness level processing part  2802  extracts the latest relatedness level recorded in the “relatedness level considering dialogue partner appropriate”, and moves the extracted relatedness level to next relatedness level. 
     The relatedness level processing part  2802  records the extracted latest relatedness level or the next relatedness level in the “relatedness level estimation recording table considering dialogue partner appropriate, based on information disclosed amount from dialogue partner”  3800 . Then, the relatedness level processing part  2802  associates the extracted latest relatedness level or the next relatedness level with the newly calculated cumulative information disclosure amount and records. Note that if the relatedness level processing part  2802  records the next relatedness level, the relatedness level processing part  2802  resets the cumulative information disclosed amount to 0. 
     (3) Details of the Relationship Adjustment Control Processing (Step S 3003 ) 
       FIG. 39  is a flowchart illustrating details of the relationship adjustment control processing. In step S 3901 , the relationship adjustment part  2803  (illustrated in  FIG. 28 ) refers to the “social behavior acceptability judgment recording table”  2600  (illustrated in  FIG. 26 ), and judges whether or not the social behavior acceptability is “Acceptable”. In step S 3901 , if the relationship adjustment part  2803  judges that the social behavior acceptability is “Acceptable”, processing proceeds to step S 3902 . 
     In step S 3902 , the relationship adjustment part  2803  performs relationship level adjustment direction control processing. 
     Specifically, the relationship adjustment part  2803  refers to the “judgment recording table of relationship level considered appropriate to dialogue partner”  3400  (illustrated in  FIG. 34 ), and extracts the relationship level newly recorded in the “relationship level considered appropriate to dialogue partner”. 
     The relationship adjustment part  2803  also refers to the “relatedness level estimation recording table considering dialogue partner appropriate, based on information disclosed amount from dialogue partner”  3800 , and extracts the relatedness level newly recorded in the “relatedness level considering dialogue partner appropriate”. 
     The relationship adjustment part  2803  also judges whether or not the extracted relationship level is identical to the extracted relatedness level. 
     If the relationship adjustment part  2803  judges that the extracted relationship level is identical, the relationship adjustment part  2803  estimates that a relationship is being built with a comparable information disclosure and at a comparable speed. In this case, the relationship adjustment part  2803  judges that the relationship adjustment direction control is not desirable and that it is not also desirable to update the dialogue strategy. 
     On the other hand, if the relationship adjustment part  2803  judges that the extracted relationship level is not identical, the relationship adjustment part  2803  judges the magnitude relationship. If the extracted relationship level is larger than the extracted relatedness level, the relationship adjustment part  2803  judges that the relationship is such controlled that the relationship level is not too close (negative direction). 
     For example, suppose that the relationship level that considers the user  150  appropriate to the user  140  (illustrated in  FIG. 1 ) is “1_intimate”. On the other hand, suppose that the relatedness level that is estimated to consider the user  140  appropriate to the user  150  is “0_superficial”. In this case, the relationship adjustment part  2803  judges that the relationship is to be controlled to the negative direction. 
     In addition, if the extracted relatedness level is larger than the extracted relationship level, the relationship adjustment part  2803  judges that the relationship level is controlled in an approaching direction (positive direction). 
     For example, suppose that the relationship level that considers the user  150  appropriate to the user  140  is “0_superficial”. On the other hand, suppose that the relatedness level that is estimated to consider the user  140  appropriate to the user  150  is “1_intimate”. In this case, the relationship adjustment part  2803  judges that the relationship is to be controlled to the positive direction. 
     (4) Details of the Dialogue Strategy Determination Processing Based on the Relationship Adjustment Control (Step S 3004 ) 
       FIG. 40  is a flowchart illustrating details of the dialogue strategy determination processing based on the relationship adjustment control. In step S 4001 , the determination part  2804  (illustrated in  FIG. 28 ) refers to the processing result of the relationship adjustment processing (step S 3003  illustrated in  FIG. 30 ) by the relationship adjustment part  2803  (illustrated in  FIG. 28 ) and judges whether or not the relationship adjustment direction control is desirable. 
     If the relationship level and the relatedness level are not identical, in step S 4001 , the determination part  2804  judges that the relationship adjustment direction control is desirable and proceeds to step S 4002 . 
     In step S 4002 , the determination part  2804  understands the current dialogue strategy and identifies a direction judged by the relationship adjustment part  2803 . 
     If the relationship level adjustment direction judged by the relationship adjustment part  2803  is in the negative direction, the determination part  2804  determines the dialogue strategy that is in more negative than the current dialogue strategy. 
     On the other hand, if the relationship level adjustment direction judged by the relationship adjustment part  2803  is in the positive direction, the determination part  2804  determines the dialogue strategy that is in more positive than the current dialogue strategy. Note that the relationship adjustment part  2803  refers to the “dialogue strategy definition data table by relationship level”  2900  (illustrated in  FIG. 29 ) in determining the dialogue strategy. 
     The presentation control section  805  (illustrated in  FIG. 8 ) records the dialogue strategy determined by the relationship adjustment part  2803  in the “recording table of dialogue strategy determination corresponding to relationship level” in the evaluation information DB 119 . 
       FIG. 41  is a diagram illustrating an example of the recording table of dialogue strategy determination corresponding to relationship level, recorded in the evaluation information DB. As illustrated in  FIG. 41  the “recording table of dialogue strategy determination corresponding to relationship level”  4100  includes the “behaving avatar ID” and “behaved avatar ID”, as the information item. In these information items are recorded the avatar ID of the user who behaves based on the dialogue strategy and the avatar ID of the user who receives the behavior based on the dialogue strategy. 
     In addition, the “recording table of dialogue strategy determination corresponding to relationship level”  4100  includes the “relationship adjustment direction control” and the “dialogue strategy”, as the information item. In these information items are recorded the direction judged by the relationship adjustment part  2803  and the dialogue strategy determined by the determination part  2804  (each illustrated in  FIG. 28 ). 
     For example, suppose that the current dialogue strategy is the “Shortly_positive” strategy that it is the default dialogue strategy the relationship level of which is “0_superficial” (dialogue strategy for which the “distance from the default strategy” is 0). In this case, if the “relationship adjustment direction control” is the negative direction, from  FIG. 29 , the dialogue strategy in the negative direction is the “Minimally_positive”. Therefore, the determination part  2804  (illustrated in  FIG. 28 ) determines the “Minimally_positive” strategy as the dialogue strategy corresponding to the relationship level. In addition, the presentation control section  805  records the “Minimally_positive” strategy in the “dialogue strategy” of the “recording table of dialogue strategy determination corresponding to relationship level”  4100 . 
     As is clear from the foregoing description, the image generation device  110  (illustrated in  FIG. 1 ) in the third embodiment, in determining the dialogue strategy, —judges or estimates the relationship level and the relatedness level with the dialogue partner, —if the social behavior acceptability is “Acceptable”, the dialogue strategy is determined so as to adjust a balance between the relationship level and the relatedness level. 
     With this, according to the image generation device  110  in the third embodiment, the reactive behavior based on the dialogue strategy determined from the standpoint of adjusting the relationship level with the dialogue partner may be presented to the dialogue partner. 
     Fourth Embodiment 
     In the foregoing first to third embodiments, the description is given on the assumption that the reactive social behavior corresponding to the dialogue strategy is predefined. To the contrary, in the fourth embodiment, description is given of a case where the reactive social behavior corresponding to the dialogue strategy is changed based on the social behavior actually performed by the user. In the following, the fourth embodiment is described, mainly focusing on differences from the foregoing first embodiment. 
     &lt;Functional Configuration of Reactive Processing Unit of Image Generation Device&gt; 
     First, description is given of the functional configuration of the reactive processing unit  115  of the image generation device  110  with reference to  FIG. 42 .  FIG. 42  is a fourth diagram illustrating the functional configuration of the reactive processing unit of the image generation device. 
     A difference from  FIG. 8  is that new tables are recorded in a presentation control section  4200 , the definition data DB  118 , and the evaluation information DB  119 . Note that of the tables depicted in the definition data DB  118  and the evaluation information DB  119  in  FIG. 42 , the tables marked with a filled circle represent the new tables. 
     As illustrated in  FIG. 42 , the presentation control section  4200  includes an execution stack registration part  4201 , synthesis part  4202 , and a control part  4203 . 
     The execution stack registration part  4201  refers to the “dialogue strategy” of the “dialogue strategy determination recording table”  1900  (illustrated in  FIG. 19 ) in the evaluation information DB  119 , and identifies the present dialogue strategy. Note that in the fourth embodiment, the execution stack registration part  4201  refers to the dialogue strategy of the user  150  to the user  140  (illustrated in  FIG. 1 ), of the dialogue strategies recorded in the “dialogue strategy” of the “dialogue strategy determination recording table”  1900 . 
     In addition, the execution stack registration part  4201  refers to a “reactive social behavior definition data table per dialogue strategy” stored in the definition data DB  118 , and judges for the current dialogue strategy whether or not the reactive social behavior is permitted. 
     If the execution stack registration part  4201  also judges that reactive social behavior is permitted, the execution stack registration part  4201  refers to a “reactive social behavior definition data table per dialogue strategy” again, and extracts the corresponding social behavior. 
     In addition, the execution stack registration part  4201  registers in an execution stack the extracted social behavior as the reactive social behavior. The execution stack is an area on the memory storing the social behavior that be performed as the reactive social behavior, and is provided separately from a “recording table of social behavior in execution stack” in the evaluation information DB  119 . Note that if more than one social behavior is extracted, the execution stack registration part  4201  refers to a “social behavior group definition data table” stored in the definition data DB  118 , and registers the extracted social behaviors as the reactive social behavior group in the execution stack. 
     Furthermore, the execution stack registration part  4201  records, in the “recording table of social behavior in execution stack” in the evaluation information DB  119 , the social behavior or the social behavior group registered in the execution stack. 
     If the user  150  performs the social behavior, the synthesis part  4202  newly registers the social behavior performed by the user  150  in the execution stack, thereby synthesizing the social behavior into the social behavior registered in the execution stack. 
     Additionally, when synthesizing the social behavior, the synthesis part  4202  refers to an “approach and avoidance tendency evaluation value definition data table of social behavior and social behavior group” stored in the definition data DB  118 . Then, after reviewing possible influence of a case of synthesizing the social behavior, the synthesis part  4202  synthesizes the social behavior into the social behavior registered in the execution stack. 
     If the user  140  performs the social behavior, based on the social behavior (or the social behavior group) registered in the execution stack, the control part  4203  such controls that the reactive social behavior is presented to the user  140 . 
     The control part  4203  also records the reactive social behavior presented to the user  140  in a social behavior control log table in the evaluation information DB  119 . 
     &lt;Description of Table Relating to Processing of Respective Components of Reactive Processing Unit&gt; 
     In the following, description is given of the table including data relating to processing of respective components (here, the presentation control section  4200 ) of the reactive processing unit  115  (illustrated in  FIG. 1 ). 
     (1) Reactive Social Behavior Definition Data Table Per Dialogue Strategy 
       FIG. 43  is a diagram illustrating an example of the reactive social behavior definition data table per dialogue strategy, stored in the definition data DB. As illustrated in  FIG. 43 , “reactive social behavior definition data table per dialogue strategy”  4300  includes, as the information item, the “dialogue strategy”, a “permission control condition of reactive social behavior”, and “recommended social behavior and social behavior group”. 
     The “dialogue strategy” defines a plurality of predefined dialogue strategies. The “permission control condition of reactive social behavior” defines a condition for permitting the reactive social behavior, for the respective dialogue strategies in the “dialogue strategy”. 
     The “recommended social behavior and social behavior group” defines the social behavior or the social behavior group to be performed if the respective dialogue strategies defined in the “dialogue strategy” are determined. 
     As depicted on the bottom row of the data rows of  FIG. 43 , suppose that a “Totally_positive” strategy is determined as the dialogue strategy. In this case, the reactive social behavior is permitted for the social behavior excluding “Gesture_NegativemeaningGesture”. Thus, the execution stack registration part  4201  registers “Approaching_seqStandard” as the reactive social behavior in the execution stack. 
     (2) Social Behavior Group Definition Data Table 
       FIG. 44  is a diagram illustrating an example of a social behavior group definition data table stored in the definition data DB. As illustrated in  FIG. 44 , the “social behavior group definition data table”  4400  includes the “social behavior group” and the “component”, as the information item. 
     The “social behavior group” defines a name for identifying the social behavior group. The “component” defines a plurality of social behaviors included in the social behavior group defined in the “social behavior group”. 
     An example on the first row of the data rows of  FIG. 44  indicates that the social behavior group identified by “Approaching_seqStandard” includes the following three types of combinations of the social behavior and the social behavior group. Note that a group that is defined as a set having as an element the combination of the social behavior and the social behavior group and that defines two or more elements is referred to as the “social behavior group”.
         “Gesture_Positivemeaninggestureto,type=nod”, “Avoiding_seqKeepaway”   “Approaching_seqMutualtry”, “Lean_Backward”,
           “Gesture_Positivemeaninggestureto”   
           “Approaching_seqMutualtry”       

     According to the example of  FIG. 44 , if the execution stack registration part  4201  (illustrated in  FIG. 42 ) registers “Approaching_seqStandard” in the execution stack, the execution stack registration part  4201  registers any of the social behavior groups listed above. 
     (3) Approach and Avoidance Tendency Evaluation Value Definition Data Table of Social Behavior and Social Behavior Group 
       FIG. 45  is a diagram illustrating an approach and avoidance tendency evaluation value definition data table of social behavior and social behavior group, stored in the definition data DB. As illustrated in  FIG. 45 , an “approach and avoidance tendency evaluation value definition data table of social behavior and social behavior group”  4500  includes an “approach and avoidance tendency evaluation value” and an “approach and avoidance tendency evaluation value determination condition”, as the information item. 
     The “approach and avoidance tendency evaluation value” defines an evaluation value to be referred when the synthesis part  4202  (illustrated in  FIG. 42 ) synthesizes the social behavior. The “approach and avoidance tendency evaluation value determination condition” defines a condition for outputting the evaluation value defined in the “approach and avoidance tendency evaluation value”. 
     In the case of the fourth data line, for example, of the data rows of  FIG. 45 , in order to output “4” as an approach tendency evaluation value, the condition is that—a length of duration (time from the recording start time to the recording end time) when the social behavior group is performed is to be 3 [seconds] or longer. 
     In addition, in the case of the fourth data row, in order to output “4” as an avoidance tendency evaluation value, the condition is that—the length of duration when the social behavior group is performed is to be 3 [seconds] or longer or that—the performed social behavior group is the social behavior group of the avoidance tendency. 
     &lt;Details of Presentation Control Processing of Reactive Processing Unit&gt; 
     In the following, details of the presentation control processing of the reactive processing unit  115  are described. Note that the presentation control processing of the reactive processing unit  115  in the fourth embodiment has the process (steps S 1501  to S 1504 ) similar to the presentation control processing described with reference to  FIG. 15  in the first embodiment. 
     Thus, here, of the presentation control processing of the reactive processing unit  115 , the process other than steps S 1501  to S 1504  is described with reference to  FIG. 46 .  FIG. 46  is a second flowchart illustrating details of the presentation control processing of the reactive processing unit. 
     As illustrated in  FIG. 46 , the presentation control processing of the reactive processing unit  115  (illustrated in  FIG. 1 ) in the fourth embodiment includes steps S 4601  to S 4603 , as the process other than steps S 1501  to S 1504 . 
     Of these, in step S 4601 , the execution stack registration part  4201  performs execution stack registration processing, in step S 4602 , the synthesis part  4202  performs synthesis processing, and in step S 4603 , the control part  4203  performs the presentation control processing based on the execution stack. In the following, details of steps S 4601  to S 4603  are described. 
     (1) Details of the Execution Stack Registration Processing (Step S 4601 ) 
       FIG. 47  is a flowchart illustrating details of the execution stack registration processing. In step S 4701 , the execution stack registration part  4201  (illustrated in  FIG. 42 ) judges whether or not the user  140  (illustrated in  FIG. 1 ) performs the social behavior. 
     In step S 4701 , if the execution stack registration part  4201  judges that the user  140  performs the social behavior, processing proceeds to step S 4702 . In step S 4702 , the execution stack registration part  4201  refers to the “dialogue strategy determination recording table”  1900  (illustrated in  FIG. 19 ) in the evaluation information DB  119  (illustrated in  FIG. 1 ), and identifies the current dialogue strategy of the user  150  to the user  140 . Here, the execution stack registration part  4201  identifies that the current dialogue strategy of the user  150  to the user  140  is the “Totally_positive strategy”. 
     Subsequently, the execution stack registration part  4201  (illustrated in  FIG. 42 ) refers to the “reactive social behavior definition data table per dialogue strategy”  4300  (illustrated in  FIG. 43 ), and judges whether the reactive behavior is permitted, for the identified current dialogue strategy. According to the “reactive social behavior definition data table per dialogue strategy”  4300 , in the case of the “Totally_positive strategy”, the reactive social behavior is permitted. 
     Thus, the execution stack registration part  4201  judges that reactive social behavior is permitted. 
     Subsequently, the execution stack registration part  4201  determines the reactive social behavior to be performed, and records the reactive social behavior in the execution stack. According to the “reactive social behavior definition data table per dialogue strategy”  4300 , in the case of the “Totally_positive strategy”, “Approaching_seqStandard” is defined as the recommended social behavior group. Thus, the execution stack registration part  4201  registers the social behavior group in the execution stack. 
     Additionally, according to “social behavior group definition data table”  4400 , “Approaching_seqStandard” includes three types of the social behavior groups. The execution stack registration part  4201  registers any of the three types of the social behavior groups in the execution stack. Any social behavior group to be registered may be randomly selected or the social behavior group the frequency of previous execution of which is low may be selected. That is, a selection criterion in selecting the social behavior group that the execution stack registration part  4201  registers in the execution stack may be arbitrary. 
     Here, suppose that the execution stack registration part  4201  registers the first social behavior group included in the “Approaching_seqStandard”. Specifically, suppose that the execution stack registration part  4201  registers “gesture_Positivemeaninggestureto,type=nod” and “Avoiding_seqKeepaway”. 
     Note that as “Avoiding_seqKeepaway” is the social behavior group, the execution stack registration part  4201  also registers in the execution stack the plurality of social behaviors included in “Avoiding_seqKeepaway” together. 
     Subsequently, the execution stack registration part  4201  records the social behavior group registered in the execution stack, in “the recording table of social behavior in execution stack” in the evaluation information DB  119 .  FIG. 48  is a first diagram illustrating an example of the recording table of social behavior in execution stack, recorded in the evaluation information DB. 
     As illustrated in  FIG. 48 , on the first and second rows of the data rows in the “recording table of social behavior in execution stack  1 ”  4800 , the elements forming “Approaching_seqStandard” are recorded. Specifically, all of the social behaviors (or the social behavior groups), which are defined as a sequence in  FIG. 44 , are recorded. Note that the elements recorded on the second row of data rows are the social behavior groups and the social behavior to be performed actually are registered in the execution stack. Thus, on the third row of data rows are recorded the plurality of social behaviors included in the social behavior group (“Avoiding_seqKeepaway”). Specifically, with reference to the sequence defined in  FIG. 44 , “Orientation_Face_Indirectto” and “Orientation_Upperbody_Indirectto” are recorded. 
     (2) Details of the Synthesis Processing (Step S 4602 ) 
       FIG. 49  is a flowchart illustrating details of synthesis processing. In step S 4901 , the synthesis part  4202  (illustrated in  FIG. 42 ) judges whether or not the user  150  (illustrated in  FIG. 1 ) performs the social behavior. 
     The synthesis part  4202  judges whether or not to synthesize into behavior being performed by the avatar the social behavior being performed by the user corresponding to the avatar. If the synthesis part  4202  judges to perform the synthesis, the synthesis part  4202  performs the synthesis of the social behavior being performed by the user corresponding to the avatar. 
     In step S 4901 , if it is judged that the user  150  performed the social behavior in the past, processing proceeds to step S 4902 . 
     In step S 4902 , the synthesis part  4202  refers to the “recording table of social behavior in execution stack  1 ”  4800  (illustrated in  FIG. 48 ). Then, the synthesis part  4202  judges whether or not the judged social behavior is already registered in the execution stack (or already performed). The synthesis part  4202  performs processing according to the judgment result of whether or not the judged social behavior is already registered in the execution stack (or already performed). Here, description is given of—a specific example of a case where the synthesis part  4202  judges that the judged social behavior is already performed (specific example 1), —the specific example of a case where the synthesis part  4202  judges that the judged social behavior is already registered but not yet to be performed (specific example 2), and—the specific examples of a case where the synthesis part  4202  judges that the judged social behavior is not yet registered (specific examples 3-1 to 4-3). 
     (a) Specific Example 1 
     For example, suppose the user  150  performs “Gesture_Positivemeaninggestureto,type=nod” as the social behavior. Then, suppose that processing to the row of an execution plan ID=“106” of the “recording table of social behavior in execution stack  1 ”  4800  is performed. In this case, the social behavior (“Gesture_Positivemeaninggestureto,type=nod”) is already recorded in the execution stack and performed. 
     Thus, the synthesis part  4202  does not record the social behavior (“Gesture_Positivemeaninggestureto,type=nod”) in the execution stack (does not perform the synthesis with the social behavior already registered in the execution stack). 
     However, the synthesis part  4202  changes “schedule intensity” in the “recording table of social behavior in execution stack  1 ”  4800 . Note that the “schedule intensity” means the intensity that the corresponding social behavior be performed and “1” is recorded as an initial value. The synthesis part  4202  changes to “2” the “schedule intensity” of the execution plan ID stating the social behavior=“Gesture_Positivemeaninggestureto,type=nod”. 
       FIGS. 50A and 50B  are second diagrams illustrating an example of the recording table of social behavior in execution stack, recorded in the evaluation information DB. Of this, a “recording table of social behavior in execution stack  2 - 1 ”  5001  in  FIG. 50A  represents how the “schedule intensity” of the execution plan ID (=“106”) is changed to “2”. 
     (b) Specific Example 2 
     For example, suppose that the user  150  (illustrated in  FIG. 1 ) performs “Orientation_Face_Indirectto” as the social behavior. Then, suppose that processing to the row of an execution plan ID=“108”) of the “recording table of social behavior in execution stack  1 ”  4800  (illustrated in  FIG. 48 ) is performed. In this case, the social behavior (“Orientation_Face_Indirectto”) is already registered in the execution stack. Thus, the synthesis part  4202  (illustrated in  FIG. 42 ) does not register the social behavior (“Orientation_Face_Indirectto”) in the execution stack (does not perform the synthesis with the social behavior already registered in the execution stack). 
     However, the synthesis part  4202  changes “schedule intensity” in the “recording table of social behavior in execution stack  1 ”  4800 . Specifically, the synthesis part  4202  changes to “2” the “schedule intensity” of the execution plan ID stating the social behavior=“Orientation_Face_Indirectto”. 
     A “recording table of social behavior in execution stack  2 - 2 ”  5002  of  FIG. 50B  represents how the “schedule intensity” of the execution plan ID (=“108”) is changed to “2”. 
     (c) Specific Example 3-1 
     For example, suppose that the user  150  performs “Attention_joint” as the social behavior. Then, suppose that processing to the row of an execution plan ID=“108”) of the “recording table of social behavior in execution stack  1 ”  4800  is performed. In this case, the social behavior (“Attention_joint”) is not yet recorded in the execution stack and performed. Thus, synthesis part  4202  registers the social behavior (“Attention_joint”) in the execution stack. 
     Note that the execution plan IDs=“106” to “108” are registered as the other social behavior (or social behavior group) in the execution stack. Thus, the synthesis part  4202  registers the social behavior (“Attention_joint”) after the other social behavior (or the social behavior group) already registered. 
     The synthesis part  4202  also records in the “recording table of social behavior in execution stack” that the social behavior is registered in the execution stack.  FIG. 51  is a third diagram illustrating an example of the recording table of social behavior in execution stack, recorded in the evaluation information DB. 
     As illustrated in  FIG. 51 , for the execution plan ID=“109” in the “recording table of social behavior in execution stack  2 - 3 ”  5100 ,
         “Attention_joint,intention=5,attributescore=5,duration9” is recorded as the social behavior. Note that if the newly social behavior is record, the initial value (“1”) is recoded for the corresponding “schedule intensity”.       

     (d) Specific Example 3-2 
     For example, suppose that the user  150  (illustrated in  FIG. 1 ) performs “Attention_joint” as the social behavior. As described in the specific example 3-1, according to the “recording table of social behavior in execution stack  1 ”  4800  (illustrated in  FIG. 48 ), the social behavior (“Attention_joint”) is not yet registered in the execution stack. Thus, the synthesis part  4202  (illustrated in  FIG. 42 ) registers the social behavior (“Attention_joint”) in the execution stack. 
     Then, the synthesis part  4202  refers to the “social behavior value calculation recording table”  1800  (illustrated in  FIG. 18 ), and calculates a value representing an attribute of the social behavior such as the length of duration (time from the recording start time to the recording end time) when the social behavior is performed) or intensity. 
     Subsequently, the synthesis part  4202  refers to the “approach and avoidance tendency evaluation value definition data table of social behavior and social behavior group”  4500  (illustrated in  FIG. 45 ), based on the calculated duration length and the approach and avoidance tendency of the social behavior, and outputs the “approach and avoidance evaluation value”. 
     Since the social behavior (“Attention_joint”) performed by the user  150  is the social behavior of the approach tendency and has the duration of 3 seconds or longer, the synthesis part  4202  obtains the approach tendency evaluation value=“4”. 
     When registering the social behavior (“Attention_joint”) performed by the user  150  in the execution stack, the synthesis part  4202  avoids changing the approach and avoidance tendency considerably from the initial registration state to the execution stack. Thus, the synthesis part  4202  also registers in the execution stack the social behavior of the opposite tendency and at the comparable level. When the social behavior=“Attention_joint”, the synthesis part  4202  registers the social behavior having the avoidance tendency evaluation value=“4” together in the execution stack, because the approach tendency evaluation value=“4”. 
     Specifically, the synthesis part  4202  registers in the execution stack the social behavior of the opposite tendency (“Lean_Upperbody_Backward”, duration=3). Here, the social behavior of the opposite tendency and at the comparable level is selected from the social behavior or the social behavior group having the same approach and avoidance tendency evaluation value. From the social behavior or the social behavior group having the approach and avoidance tendency evaluation value of “4” in  FIG. 45 , here, the social behavior that matches the condition for Avoiding_*if (duration&gt;−3) is searched. Selection in this manner of the social behavior or the social behavior group of the opposite tendency that is registered in the execution stack and matches the condition may be determined by referring to the past social behavior value calculation recording table or a default value may be determined. 
     The synthesis part  4202  records in the “recording table of social behavior in execution stack” that the social behavior performed by the user  150  and the social behavior of the opposite tendency and at the comparable level to the social behavior are registered in the execution stack.  FIG. 52  is a fourth diagram illustrating an example of the recording table of social behavior in execution stack, recorded in the evaluation information DB. 
     As illustrated in  FIG. 52 , in the “recording table of social behavior in execution stack  2 - 4 ”  5200  are recorded the social behavior (“Attention_joint”) performed by the user  150  (illustrated in  FIG. 1 ), as the execution plan ID=“109” 
     Furthermore, the social behavior of the opposite tendency (“Lean_Upperbody_Backward, duration=3”) is recorded as the execution plan ID=“109”. Note that if the social behavior is recorded newly, the initial value (“1”) is recorded in the corresponding “schedule intensity”. 
     (e) Specific Example 4-1 
     For example, suppose that the user  150  performs “Attention_joint” as the social behavior. The processing to the execution plan ID=“106” in the “recording table of social behavior in execution stack  1 ”  4800  (illustrated in  FIG. 48 ) is performed, and the social behavior is not yet registered in the execution stack. Thus, the synthesis part  4202  (illustrated in  FIG. 42 ) registers the social behavior (“Attention_joint”) in the execution stack. Then, the synthesis part  4202  deletes and then registers the social behavior (or the social behavior group) before being performed from the social behaviors (or the social behavior groups) already registered in the execution stack. 
     Specifically, the synthesis part  4202  refers to the “recording table of social behavior in execution stack  1 ”  4800 , and identifies the social behavior and the social behavior group that are recorded in the “execution stack of social behavior and social behavior group” and not yet performed. Then, the synthesis part  4202  deletes the identified unprocessed social behavior and social behavior group from the execution stack. Specifically, the synthesis part  4202  deletes from the execution stack the social behavior (or the social behavior group) corresponding to the execution plan IDs=“107” and “108”. 
     Subsequently, the synthesis part  4202  registers “Attention_joint, intention=5, attributescore=5, duration9” in the execution stack. 
     The synthesis part  4202  also records in the “recording table of social behavior in execution stack” that the social behavior already registered in the execution stack are deleted and that the social behavior newly performed by the user  150  is registered in the execution stack. 
       FIG. 53  is a fifth diagram illustrating an example of the recording table of social behavior in execution stack, recorded in the evaluation information DB. 
     As illustrated in  FIG. 53 , in the “recording table of social behavior in execution stack  2 - 5 ”  5300 , the execution plan IDs=“107” and “108” following the executed execution plan ID “106” is deleted. Then, the social behavior (Attention_joint, intention=5, attributescore=5, duration9) performed by the user  150  (illustrated in  FIG. 1 ) is newly recorded as the execution plan ID=“107” 
     (f) Specific Example 4-2 
     In the foregoing specific example 4-1, unexecuted social behavior (or the social behavior group) already registered in the execution stack is deleted, and then, the social behavior performed by the user  150  is newly registered in the execution stack. In contrast to this, in the specific example 4-2, description is given of a first case where the effect of deletion of the social behavior (or the social behavior group) is minimized and the social behavior is newly registered. 
     As depicted in the “recording table of social behavior in execution stack  1 ”  4800  (illustrated in  FIG. 48 ) is registered the unexecuted social behavior (or the social behavior group) represented in the execution plan ID=“107”, “108”. 
     The synthesis part  4202  (illustrated in  FIG. 42 ) deletes the unexecuted social behavior (or social behavior group) represented in the execution plan ID=“107”, “108”. Subsequently, the synthesis part  4202  registers “Attention_joint, intention=5, attributescore=5, duration9” in the execution stack. 
     Furthermore, the synthesis part  4202  records in the “recording table of social behavior in execution stack” that the social behavior already registered in the execution stack is deleted and that the social behavior newly performed by the user  150  is registered in the execution stack. The preceding steps are same as the foregoing specific example 4-1, and at this point in time, the “recording table of social behavior in execution stack” is same as the “recording table of social behavior in execution stack  2 - 5 ”  5300  as illustrated in  FIG. 53 . 
     Here, the synthesis part  4202  adds and registers the social behavior (or the social behavior group) to minimize the effect of the deletion of the social behavior (or the social behavior group). 
     Specifically, the synthesis part  4202  first refers to a “reactive social behavior group being executed” of this point in time (here, description is given of a case where there exists the “reactive social behavior group being executed”). Note that at this time, “Approaching_seqStandard” is recorded in the “reactive social behavior group being executed”. 
     Subsequently, the synthesis part  4202  confirms the component included in “Approaching_seqStandard” recorded in the “reactive social behavior group being executed”. The synthesis part  4202  also compares the confirmed component with the social behavior (or the social behavior group) recorded at this time in the “execution stack of social behavior and social behavior group”. 
     Based on the comparison result, the synthesis part  4202  judges whether the component of “Approaching_seqStandard” includes the social behavior (or the social behavior group) recorded in the “execution stack of social behavior and social behavior group”. 
     At this time, in the “execution stack of social behavior and social behavior group” are recorded, as the social behavior,
         “Gesture_Positivemeaninggestureto,type=nod”,   “Attention_joint,intention=5,attributescore=5,duration9”.       

     Then, a sequence of the two social behaviors is not included in “Approaching_seqStandard”. 
     Thus, the synthesis part  4202  judges that all the social behaviors or social behavior groups recorded in the “execution stack of social behavior and social behavior group” are not included as the component of “Approaching_seqStandard”. In this case, the synthesis part  4202  refers to the “reactive social behavior definition data table per dialogue strategy”  4300 . 
     Then, the synthesis part  4202  performs a comparison similar to the foregoing comparison targeted for the social behavior (or the social behavior group) recorded as “recommended social behavior and social behavior group” associated with the current dialogue strategy. Here, suppose that all the social behaviors or social behavior groups recorded in the “execution stack of social behavior and social behavior group” is included as the component of the “execution stack of social behavior and social behavior group”. In this case, the synthesis part  4202  adds and registers the social behavior and the social behavior group not included in the execution stack, of the components of the “recommended social behavior and social behavior group”. 
     On the other hand, the synthesis part  4202  judges that the component included in “Approaching_seqstandard” includes the social behavior (social behavior group) recorded in the “execution stack of the social behavior and social behavior group”. 
     In this case, the synthesis part  4202  registers in the execution stack any components other than the components that are the components included in “Approaching_seqStandard” and judged as already being included. Specifically, the synthesis part  4202  additionally registers—the social behavior group (“Avoiding_seqKeepaway”), and—the components (“Orientation_Face_Indirectto” and “Orientation_Upperbody_Indirectto”) of that social behavior group. 
     Subsequently, the synthesis part  4202  records the “deletion of the social behavior”, registration of the social behavior performed by the user  150 , and the additional registration of the social behavior in the “recording table of social behavior in execution stack”. 
       FIG. 54  is a sixth diagram illustrating an example of the recording table of social behavior in execution stack, recorded in the evaluation information DB. 
     As illustrated in  FIG. 54 , in the “recording table of social behavior in execution stack  2 - 6 ”  5400 , the execution plans IDs=“107” and “108” following the executed execution plan ID=“106” are deleted. Then, the social behavior (Attention_joint, intention=5, attributescore=5, duration9) that is performed by the user  150  (illustrated in  FIG. 1 ) as the execution plan ID=“107” is recorded. 
     Furthermore, in the execution plan IDs=“108” and “109” are recorded as the additionally registered social behaviors:
         “Avoiding_seqKeepaway”   “Orientation_Face_Indirectto”   “Orientation_Upperbody_Indirectto”.       

     (g) Specific Example 4-3 
     In the foregoing specific example 4-1, the unexecuted social behavior (or the social behavior group) already registered in the execution stack is deleted and then the social behavior newly performed by the user  150  is registered in the execution stack. On the other hand, in the specific example 4-2, description is given of the case where the following sequence matches the component of the reactive social behavior group being executed or the component of the recommended social behavior and the social behavior group:—“Gesture_Positivemeaninggestureto, type=nod”, —“Attention_joint, intention=5, attributescore=5, duration9”. Note that foregoing sequence is the sequence registered in the “execution stack of the social behavior and social behavior group”. 
     In contrast to this, in the specific group  4 - 3 , description is given of a case that does not match any of the foregoing cases. Specifically, description is given of a case where paired social behaviors having the evaluation value that is in the direction opposite to and at the level comparable with the social behavior registered in the “execution stack of the social behavior and social behavior group” are recorded in the execution stack. 
     With the processing up to the row of the execution plan ID=“106” in the “recording table of social behavior in execution stack  1 ”  4800  (illustrated in  FIG. 48 ) executed, the unexecuted social behavior (or the social behavior group) represented by the execution plan ID=“107” and “108” are registered in the execution stack. 
     The synthesis part  4202  (illustrated in  FIG. 42 ) deletes the unexecuted social behavior (or the social behavior group) represented by the execution plan IDs=“107” and “108”. Subsequently, the synthesis part  4202  records “Attention_joint, intention=5, attributescore=5, duration9” in the execution stack. 
     Furthermore, the synthesis part  4202  records in the “recording table of social behavior in execution stack” that the social behavior already registered in the execution stack is deleted and that the social behavior newly performed by the user  150  is registered in the execution stack. The preceding steps are same as the foregoing specific example 4-1, and at this point in time, the “recording table of social behavior in execution stack” is same as the “recording table of social behavior in execution stack  2 - 5 ”  5300  as illustrated in  FIG. 53   
     Here, the synthesis part  4202  pairs and additionally registers the social behaviors (or the social behavior groups) in the opposite direction, to minimize the effect of the deletion of the social behavior (or the social behavior group). 
     Specifically, the synthesis part  4202  first refers to the “execution stack of the social behavior and social behavior group” of this point in time. Note that at this time, in the “execution stack of the social behavior and social behavior group” are recorded as the social behavior
         “Gesture_Positivemeaninggestureto, type=nod”   “Attention_joint, intention=5, attributescore=5, duration9”.       

     Subsequently, the synthesis part  4202  refers to the “approach and avoidance tendency evaluation value definition data table of social behavior and social behavior group”  4500  (illustrated in  FIG. 45 ). Then, the synthesis part  4202  extracts the social behavior (or the social behavior group) having the evaluation value at the level comparable with and in the direction opposite to the social behavior (or the social behavior group) recorded in the “execution stack of the social behavior and social behavior group” of this point in time. 
     Specifically, the synthesis part  4202  extracts the social behavior having the evaluation value at the level comparable with and in the direction opposite to the social behavior=“Gesture_Positivemeaninggestureto, type=nod”. With this, the synthesis part  4202  extracts “Lean_Upperbody_Backward, intention=2”. 
     The synthesis part  4202  also extracts the social behavior having the evaluation value at the level comparable with and in the direction opposite to the social behavior=“Attention_joint, intention=5, attributescore=5, duration9”. With this, the synthesis part  4202  extracts “Avoiding_seqKeepaway”. 
     Subsequently, the synthesis part  4202  records deletion of the social behavior, registration of the social behavior performed by the user  150 , and additional registration of the social behavior in the “recording table of social behavior in execution stack”. 
       FIG. 55  is a seventh diagram illustrating an example of the recording table of social behavior in execution stack, recorded in the evaluation information DB. 
     As illustrated in  FIG. 55 , in the “recording table of social behavior in execution stack  2 - 7 ”  5500 , the execution plan IDs=“107” and “108” following the executed execution plan ID=“106” are deleted. Then, the social behavior (Attention_joint, intention=5, attributescore=5, duration9) that is performed by the user  150  (illustrated in  FIG. 1 ) as the execution plan ID=“107” is recorded. 
     In addition, the additionally registered behavior (“Lean_Upperbody_Backward, intention=2”) is recorded in the execution plan ID=“108”. Furthermore, in the execution plan IDs=“109” and “110” are recorded as the additionally registered social behavior
         “Avoiding_seqKeepaway”   “Orientation_Face_Indirectto” and “Orientation_Upperbody_Indirectto”.       

     (3) Details of the Presentation Control Processing Based on the Execution Stack (Step S 4603 ) 
       FIG. 56  is a flowchart illustrating details of the presentation control processing based on the execution stack. In step S 5601 , the control part  4203  (illustrated in  FIG. 42 ) performs the social behaviors registered in the execution stack in the order of the execution plan IDs. The control part  4203  also sequentially generates the avatar images based on the social behaviors registered in the execution stack, and transmits the avatar images to the information display processing section  112  (illustrated in  FIG. 1 ). Furthermore, the control part  4203  instructs the information display processing section  112  to change the avatar image to be incorporated in the virtual space. 
     This allows the information display processing section  112  to incorporate the avatar image generated based on the sensor data obtained by sensing the actual behavior of the user  150  (illustrated in  FIG. 1 ). 
     In step S 5602 , the control part  4203  records the reactive social behavior presented to the user  140  (illustrated in  FIG. 1 ) in the social behavior control log table in the evaluation information DB  119  (illustrated in  FIG. 1 ). 
       FIG. 57  is a diagram illustrating an example of the social behavior control log table recorded in the evaluation information DB. As illustrated in  FIG. 57 , the “social behavior control log table”  5700  includes, as the information item, the “behaving avatar ID” and the “behaved avatar ID”. In these information items are respectively recorded the avatar ID of the user who performs the reactive social behavior and the avatar ID of the user who receives the reactive social behavior. 
     The “social behavior control log table”  5700  also includes, as the information item, an “execution plan ID of social behavior performed from execution stack”. In the information item is recorded the execution plan ID that is registered in the execution stack and performed as the reactive social behavior. 
     As is clear from the foregoing description, the image generation device  110  in the fourth embodiment changes the reactive social behavior per dialogue strategy based on the social behavior actually performed by the user. This allows the image generation device  110  (illustrated in  FIG. 1 ) in the fourth embodiment to present to the dialogue partner the reactive social behavior following the real social behavior of the user. 
     Other Embodiment 
     In the image generation system  100  (illustrated in  FIG. 1 ) in the foregoing first to fourth embodiments, description is given on the assumption that the image generation device  110  has the basic function unit. That is, description is given that the image generation device  110  generates the avatar images of the users  140 ,  150  based on the sensor data received from the client-side systems  120 ,  130 , and transmits the information in the virtual space to the client-side systems  120 ,  130  (each illustrated in  FIG. 1 ). 
     However, the system configuration of the image generation system is not limited thereto, and the client-side systems  120 ,  130  may each have the basic function unit to generate the virtual space information. In this case, the client-side system  120  transmits a copy of the avatar image of the user  140  to the client-side system  130  and the client-side system  130  incorporates the avatar image of the user  140  in the generated virtual space information. 
     Similarly, the client-side system  130  transmits a copy of the avatar image of the user  150  to the client-side system  120  and the client-side system  120  incorporates the copy of the avatar image of the user  150  in the generated virtual space information. 
     Under such a system configuration, the reactive processing unit  115  is also placed in each of the client-side systems  120 ,  130 . In addition, the dialogue strategy determination recording table of the user  140  for the user  150  is transmitted in advance to the client-side system  130 , the dialogue strategy determination recording table being generated by the reactive processing unit  115  placed in the client-side system  120 . This allows the client-side system  130  to present to the user  150  the reactive social behavior by the user  140 . 
     Similarly, the dialogue strategy determination recording table of the user  150  for the user  140  is transmitted to the client-side system  120 , the dialogue strategy determination recording table being generated by the reactive processing unit  115  placed in the client-side system  130 . This allows the client-side system  120  to present to the user  140  the reactive social behavior by the user  150 , without querying the image generation device  110 . 
     All examples and conditional language provided herein are intended for the pedagogical purposes of aiding the reader in understanding the invention and the concepts contributed by the inventor to further the art, and are not to be construed as limitations to such specifically recited examples and conditions, nor does the organization of such examples in the specification relate to a showing of the superiority and inferiority of the invention. Although one or more embodiments of the present invention have been described in detail, it should be understood that the various changes, substitutions, and alterations could be made hereto without departing from the spirit and scope of the invention.