Abstract:
A method of implicitly forming a context in a dialogue with a computer includes forming megacategories linking one or more attributes to one of a plurality of response templates. The method also includes determining a megacategory by comparing attributes having true variables from a previous input to attributes having true variables in the present input and selecting an appropriate response template corresponding to the megacategory.

Description:
TECHNICAL FIELD  
         [0001]    This invention relates to artificial intelligence and more particularly to machines that can use artificial intelligence to converse with humans.  
         BACKGROUND  
         [0002]    Since the development of the computer, human beings have sought to construct computers that can think like humans to the degree that these machines have an “artificial intelligence.” One of the goals is to develop a computer that could think, learn and carry-on intelligent conversations with humans beings.  
           [0003]    Some development of artificially intelligent computers focuses on developing computers that can converse. Thus, a key area in developing an artificially intelligent computer is developing a language that allows a computer to process inputs received from humans and to respond with an appropriate and cogent output. One such language is an Artificial Intelligence Mark-up Language (AIML) developed by Dr. Richard S. Wallace.  
           [0004]    AIML is interpreted and processed by an engine called A.L.I.C.E. (Artificial Linguistic Internet Computer Entity). The A.L.I.C.E. engine is designed to receive an input from the user and determine the correct response using knowledge encoded in AIML and stored in a AIML knowledge base. For example, when the input is, “What is two plus two?,” the A.L.I.C.E. engine provides the response, “4.” In arriving at the response of “4,” the A.L.I.C.E. engine searches a list of categories within the AIML knowledge base. Each category contains a pattern that is linked to a single response template. The A.L.I.C.E. engine matches the user input against the available patterns in the AIML knowledge base. After finding a match in a pattern, the pattern&#39;s corresponding response template is activated and a series of actions are carried out by the A.L.I.C.E. engine.  
         SUMMARY  
         [0005]    In one aspect the invention is a method of implicitly forming a context in a dialogue with a computer. The method includes forming megacategories linking one or more attributes to one of a plurality of response templates. The method also includes determining a megacategory by comparing attributes having true variables from a previous input to attributes having true variables in the present input, and selecting an appropriate response template corresponding to the megacategory.  
           [0006]    In another aspect, the invention is an article that includes a machine-readable medium that stores executable instructions for forming a context in a dialogue with a computer. The instructions cause a machine to form megacategories linking one or more attributes to one of a plurality of response templates. The instructions also cause a machine to determine a megacategory by comparing attributes having true variables from a previous input to attributes having true variables in the present input, and select an appropriate response template corresponding to the megacategory.  
           [0007]    In a still further aspect, the invention is an apparatus that includes a memory that stores executable instructions forming a context in a dialogue with a computer. The apparatus also includes a processor that executes the instructions to form megacategories linking one or more attributes to one of a plurality of response templates. The processor also executes instructions to determine a megacategory by comparing attributes having true variables from a previous input to attributes having true variables in the present input, and to select an appropriate response template corresponding to the megacategory.  
           [0008]    One or more aspects above may have one or more of the following features. Each aspect may include determining which attributes have patterns that match portions of a user&#39;s present input to the dialogue with each attribute having a variable used to record whether a match exists. Each aspect may also include marking a variable of attributes true for those attributes having matched patterns. Each attribute may be associated with a set of patterns and each pattern within the set of patterns may be semantically equivalent. Each aspect may also include storing a list of matched attributes for each user input.  
           [0009]    One or more of the aspects above have one or more of the following advantages. Enhanced artificial intelligence language engine can accept knowledge base data from existing languages such as AIML code. The enhanced artificial intelligence language allows for the implicit recognition of contextual information. The enhanced artificial intelligence language extends the pattern matching capabilities of AIML, and allows knowledge base developers to reuse portions of a knowledge base for generating other knowledge bases. Since the enhanced artificial intelligence language is a modular language, portions of the knowledge base can be modified without modifying the entire knowledge base. 
       
    
    
     DESCRIPTION OF THE DRAWINGS  
       [0010]    [0010]FIG. 1 is a system for processing an enhanced artificial intelligence language.  
         [0011]    [0011]FIG. 2 is a diagram of the relationship between attributes and response templates in the enhanced artificial intelligence language (EAIL).  
         [0012]    [0012]FIG. 3 is a process for generating a response.  
         [0013]    [0013]FIG. 4 is an initialization process.  
         [0014]    [0014]FIG. 5 is an example of an attribute trie used in determining matching patterns.  
         [0015]    [0015]FIG. 6 is an example of a megacategory trie used in selecting a response template.  
         [0016]    [0016]FIG. 7 is a process for processing an input.  
         [0017]    [0017]FIG. 8 is a process for selecting a response template. 
     
    
     DESCRIPTION  
       [0018]    Referring to FIG. 1, an enhanced artificial intelligence language (EAIL) engine  10 , within a system  12  (e.g., a computer), is used to process user inputs and to generate appropriate responses using a process  60  (FIG. 3). EAIL engine  10  includes a processor  18 , a graphical user interface (GUI)  20 , a memory  22 , and a storage medium  26  (e.g., a hard disk). Storage medium  26  stores a set of computer instructions  30 , an operating system  34  and an EAIL knowledge base  36 . EAIL knowledge base  36  includes attributes  38 , megacategories  40  and response templates  42 . Each of the components within knowledge base  36  is further discussed below. A knowledge base forms a unique artificial personality.  
         [0019]    EAIL engine  10  receives a user&#39;s inputs. The user inputs a question or statement using an input/output (I/O) interface, such as a keyboard  44  and/or a mouse  46 , using a GUI  20 . GUI  20  renders a computer image of a cyber personality on display  48  to give a user a semblance of an intelligent entity. For example, the cyber personality could be a human 3-dimensional face. The set of computer instructions  30  is executed by processor  18  out of memory  22  to process the inputs using knowledge base  36  to determine the matching megacategory in order to generate an appropriate response.  
         [0020]    Referring to FIG. 2, in EAIL engine  10 , a pattern is not necessarily tied to a single response template  52 . Instead, EAIL engine  10  includes attributes  54 . An attribute  54  has a set of patterns  50  that are semantically (though not syntactically) equivalent within an attribute  54 . Each attribute is the association of a pattern of letters with their meaning. For example, a “hello” attribute contains a sequence of letters that have been defined to mean hello (e.g., hi, howdy, bonjour, etc.).  
         [0021]    In EAIL engine  10 , categories link attributes  54  to response templates  52  using Boolean expressions. In these expressions, the atomic propositions are attributes  38 . Categories that use combinations of attributes, instead of a single pattern, are called megacategories  40 .  
         [0022]    Since multiple attributes can be used in combination, the structure of EAIL knowledge base  36  includes attributes, and response templates and a set of rules for mapping attributes to response templates. By decoupling patterns from responses, and grouping them into semantically equivalent attributes, it is easier to re-use patterns for knowledge bases with different artificial personalities.  
         [0023]    EAIL  10  searches attributes to match the input to the appropriate attribute. Even when no megacategories match (i.e., no Boolean expression evaluated is true), EAIL engine  10  looks at the attributes that matched the previous input. These attributes can be used in conjunction with the attributes that matched the current input. Thus, EAIL engine  10  can determine context without the knowledge base coder having to explicitly set variables beforehand.  
         [0024]    EAIL engine  10  has a modular approach, where a set of attributes can be generated and distributed without having any affect on any one artificial personality. Since pattern matching in EAIL engine  10  is done independently of megacategories, multiple wildcards and more general regular expression operators can be added while still employing most of AIML&#39;s category selection algorithm.  
         [0025]    I. EAIL Knowledge Base Overview  
         [0026]    A. EAIL Knowledge Base Syntax  
         [0027]    EAIL uses an XML-based format to encode knowledge. EAIL files have an “.eail” extension and have a root element named &lt;eail&gt;. A partial document type definition (DTD) for EAIL appears below. The definition of the contents of the &lt;template&gt; tag and the &lt;category&gt; tag, not shown, are identical to their AIML  1 . 0  analogs except for the &lt;star&gt; tag.  
                                                                                                     &lt;!ELEMENT eail (attribute*, category*, megacategory*,                topic*)&gt;                &lt;!ELEMENT attribute (pattern+)&gt;           &lt;!ELEMENT megacategory (that, expr, template)&gt;           &lt;!ELEMENT topic (category*, megacategory*)&gt;           &lt;!ELEMENT pattern (#PCDATA)&gt;           &lt;!ELEMENT that (#PCDATA)&gt;           &lt;!ELEMENT expr (#PCDATA)&gt;           &lt;!ATTLIST attribute                name CDATA #REQUIRED&gt;                &lt;!ATTLIST megacategory                level CDATA #IMPLIED&gt;           &lt;!ATTLIST pattern           sindex CDATA #IMPLIED&gt;                      
 
         [0028]    B. Attributes  
         [0029]    Each attribute  38  in EAIL knowledge base  36  has a name and a set of one or more patterns  40 . The name of an attribute may be any combination of letters, numbers and an underscore. One or more of the following symbols may appear in a pattern. An “*” symbol, (asterisk) , denotes a wildcard and matches one or more words in the input. An “_” symbol, (underscore), is also a wildcard, and provides the same function as the asterisk except the underscore lexicographically precedes all alphanumeric characters, whereas the asterisk follows alphanumeric characters. A “?” symbol, (question mark), immediately after a word makes the word optional. A “{ . . . | . . . }” symbol represents series of words that appear between “{” and “}” and are separated by “|” to denote a selection of one of the words in the series. A “%” symbol, a percent symbol, can appear immediately before or after a word to show that the word can be a sub-string of a word in the input. For example, “%comfort%” would match “comfort,” “comfortable”, and “uncomfortable”.  
         [0030]    Each pattern may also have a “sindex” attribute. The “sindex” attribute is used to determine which asterisk to use when the &lt;star&gt; tag appears in a response template. Since there are multiple wildcards in a pattern, ambiguity can arise unless it is clear which wildcard is meant to be used. In the absence of this attribute, the value 1 is assumed (1 is the first wildcard, not 0).  
         [0031]    C. Megacategories  
         [0032]    Each megacategory  40  links a combination of attributes  38  to a single response template  42 . The combination is represented by an expression having attributes&#39; names, the AND operator (&amp;&amp;), and the OR operator (||). Parentheses are allowed, but the unary NOT (!) is not allowed. These expressions will be converted to disjunctive normal form by EAIL engine  10  for efficient evaluation.  
         [0033]    Each megacategory may optionally have a “that” tag, which is semantically equivalent to the “that” tag in AIML categories. The “that” tag contains a pattern that matches against a previous artificial personality output that allows a programmer to put in different responses to the same input based on what the artificial personality just said. For example, a programmer wants to program a knock-knock joke. The artificial personality will start by saying “knock, knock.” Then the user will say “Who&#39;s there?” When programming a response to the pattern “Who&#39;s there?,” the programmer would put a “that” tag in with the pattern “knock, knock.” If the programmer leaves out the “that” tag, the artificial personality will try to tell knock-knock jokes any time the user says “Who&#39;s there?,” which is not the desired behavior. For instance, if the artificial personality says “I&#39;m going to visit someone in Florida,” and the user says “Who&#39;s there?,” it would be inappropriate for the artificial personality to tell a knock-knock joke.  
         [0034]    A programmer designing knowledge base  36  may also optionally assign a level to each megacategory. Giving megacategories different levels imposes an explicit hierarchy on the order in which megacategories are evaluated by EAIL engine  10 . As a default, all megacategories are set at level one. All megacategories of level one are considered before megacategories of level  2 , and all megacategories of level  2  are considered before megacategories of level  3 , etc.  
         [0035]    The response template for a megacategory is identical to the response template for an AIML category, except in the treatment of the &lt;star&gt; tag. Since there are possibly multiple attributes working together in a megacategory, the &lt;star&gt; tag references the name of the attribute that contains the wildcard it is referencing. Within the attribute, the pattern tag contains information about which specific asterisk to use (i.e., “sindex” attribute). When multiple patterns within an attribute match the input, and they all have a “sindex” attribute, the pattern with the highest specificity rank has precedent.  
         [0036]    D. Categories  
         [0037]    Categories have the same knowledge that was originally intended for use by an AIML engine. In order to be used in an EAIL knowledge base, each category is converted to an equivalent combination of an attribute and a megacategory. This conversion is carried out by EAL engine  10 , and is transparent to the knowledge base code developer.  
         [0038]    E. Topics  
         [0039]    Megacategories and categories can be grouped into topics, which are identical to topics in AIML. A topic is identified by its name. A special “topic” variable may be set in a response template. Megacategories and categories that appear within a &lt;topic&gt; tag will only match when the topic variable matches the name of the topic.  
         [0040]    II. EAIL Engine Processes  
         [0041]    A. Category Conversion  
         [0042]    Referring to FIGS. 3 and 4, process  60  performs ( 62 ) an initialization using a process  80 . Process  80  converts ( 84 ) all of the AIML categories in EAIL knowledge base  36  that were intended for the A.L.I.C.E. AIML interpreter, to EAIL megacategories  40 , before any patterns are matched or any response is generated. Each category includes a pattern and a response template. A new attribute, with an automatically generated name, is generated with the one pattern. A new megacategory is also generated having the same response template as the original category (with &lt;star&gt; expressions converted to be compatible with EAIL). The expression is the name of the newly generated attribute. For example, given:  
                                                   &lt;category&gt;           &lt;that&gt;WHAT CAN I HELP YOU WITH&lt;/that&gt;           &lt;pattern&gt;PLEASE *&lt;/pattern&gt;           &lt;template&gt;&lt;srai&gt;&lt;star/&gt;&lt;/srai&gt;&lt;/template&gt;           &lt;/category&gt;                      
 
         [0043]    is converted into:  
                                                                       &lt;attribute name=“abcd”&gt;           &lt;pattern sindex=“1”&gt;PLEASE *&lt;/pattern&gt;           &lt;/attribute&gt;           &lt;megacategory&gt;           &lt;that&gt;WHAT CAN I HELP YOU WITH&lt;/that&gt;           &lt;expr&gt;abcd&lt;/expr&gt;           &lt;template&gt;&lt;srai&gt;&lt;star                attribute=“abcd”/&gt;&lt;/srai&gt;&lt;/template&gt;                &lt;/megacategory&gt;                      
 
         [0044]    where “abcd” is an automatically generated name for the attribute.  
         [0045]    Matching the patterns to the appropriate response is data in which there is one node for every common prefix. The strings are stored in extra leaf nodes.  
         [0046]    An attribute trie structure is generated during EAIL engine initialization. The trie has all of the patterns from within all the attributes in EAIL knowledge base  36 . Before the patterns are inserted into the attribute trie, process  80  expands ( 86 ) the patterns into patterns that do not contain any ‘{ . . . | . . . }’ or ‘?’ symbols. These symbols are removed by generating a set of patterns that as a whole perform the same function before removing any symbols. For instance, the pattern “A B?C” is expanded into two patterns: “A C” and “A B C”. In another instance, the pattern “A {B |C}” is expanded to “A B” and “A C”. In addition to the expansion, a special ‘$’ symbol is appended to each pattern, to represent the end of the input.  
         [0047]    Process  80  arranges ( 88 ) all of the patterns in the knowledge base  36  in alphabetical order. Process  80  assigns ( 90 ) a specificity rank that represents its position within the alphabetical list. The specificity rank is used to determine a pattern&#39;s “specificity” in relation to other patterns when choosing between multiple matching megacategories as described below (see FIG. 8). Process  80  adds ( 92 ) each pattern to a trie to form an attribute trie.  
         [0048]    The following is one example to generate an attribute trie:  
                                                                                                                                             for each pattern in set           current_node := root           for each word w in pattern                if (branch exists from current_node on w)                current_node := node attached to branch           continue                else                generate new_node           generate a branch from current_node to                new_node on w                current_node := new node                end if                end for                set current_node to be a “match” node           end for                      
 
         [0049]    [0049]FIG. 5 shows a finished attribute trie  120  for the patterns “WHEN * START $” and “WHEN * BEGIN $”. Each box above represents a node  122 , and each arrow represents a branch  124 . Nodes with a ‘m’ in their name (nodes  4  and  6 ) are match nodes  126 . As will be described further below, reaching these matched nodes, during a traversal of the attribute trie, indicates that a pattern has been matched.  
         [0050]    During initialization a “that” trie is generated similarly to the attribute trie. Process  80  expands ( 94 ) the “that” patterns. Process  80  arranges ( 96 ) the “that” patterns alphabetically. Process  80  assigns ( 98 ) a specificity rank to each “that” pattern. Process  80  adds ( 100 ) each pattern to a trie to form a “that” trie.  
         [0051]    During initialization a megacategory trie is also generated. Process  80  expands ( 102 ) expressions in the megacategories into the disjunctive normal form. Process  80  orders ( 104 ) the conjunctions alphabetically. Process  80  adds ( 106 ) each conjunction to a trie to form a “megacategory” trie. A separate trie for each “level” of megacategories in the EAIL knowledge base is generated.  
         [0052]    For example of generating a megacategory trie, consider a megacategory that has the expression “C &amp;&amp; (A ||B)”, a “that” tag, and a topic. A variable is generated by EAIL engine  10  for both the “that” tag and the topic. Suppose the variable for the “that” tag is “D” and the variable for the topic is “E”. EAIL engine  10  “AND&#39;s” the original expression with both variables. The expression becomes “((C &amp;&amp; (A ||B)) &amp;&amp; D) &amp;&amp; E”.  
         [0053]    This compound expression is expanded to the DNF. In this example, the resulting expression would be “(C &amp;&amp; A &amp;&amp; D &amp;&amp; E) ||(C &amp;&amp; B &amp;&amp; D &amp;&amp; E)”. Each conjunction is ordered alphabetically by variable name, so each conjunction now becomes “(A &amp;&amp; C &amp;&amp; D &amp;&amp; E) ||(B &amp;&amp; C &amp;&amp; D &amp;&amp; E)”. The conjunctions (two in all for this example) are added to a trie (not shown) constructed similarly to trie  128  in FIG. 6. Each matching node maintains a link to the megacategory with which it is associated.  
         [0054]    B. Processing an Input  
         [0055]    Referring to FIGS. 3 and 7, process  60  processes ( 54 ) an input using a process  130  by traversing the tries (e.g., attribute trie, that trie, and megacategory trie) generated during initialization (e.g., process  80 ). Process  130  receives ( 132 ) an input.  
         [0056]    To traverse the attribute trie, process  130  divides ( 134 ) the input up into words. Punctuation is removed and spaces between words in the input are treated as a word delimiter. Process  110  appends ( 136 ) the words with a ‘$’ symbol.  
         [0057]    Process  110  traverses ( 138 ) the attribute trie with the input to obtain a list of matching attributes. One example of traversing the attribute trie uses the following:  
                                                                                                                                                                                                                   procedure findPatterns(input)                findPatterns(root, input, 0);                end procedure           procedure findPatterns(current_node, input, pos+2)                if (current_node is match node)                pattern found                end if           cur_word := word at position pos in input           for each branch from current_node on cur_word                new_node = node attached at branch           findPatterns(new_node, input, pos+1)                end for           if (branch exists from current node on “*” or “_”)                new_node = node attached at branch           resolveWildCard(new_node, input, pos)                end if                end procedure           procedure resolveWildCard(current_node, input, pos)                for each word w in input starting at position pos                if (branch exists from current_node on w)                new_node = node attached at branch           new_pos := position of w in input           findPatterns(new_node, input, new_pos)                end if                end for                end procedure                      
 
         [0058]    Process  130  traverses ( 140 ) the “that” trie with the previous output of EAIL engine  10  to obtain a list of matching “that” patterns.  
         [0059]    Process  130  traverses ( 142 ) the megacategory trie with matched attributes and matched “that” patterns (and with topic variables if applicable) to obtain a list of matching megacategories. In traversing trie  128 , the following is used to find all matching expressions:  
         [0060]    procedure find Expressions (vars_list)  
                                                                                                                                                                 for pos1 := 0 to length of vars_list                current_node := root           for pos2 := pos1 to length of vars_list                var := variable at pos2 in vars_list           if (current_node is match)                matching expression found                end if           if (branch exists from current_node on var)                current_node := node attached at branch                else                break                end if                end for                end for                end procedure                      
 
         [0061]    Each generated level of megacategory trie is traversed. The megacategory tries corresponding to level one are traversed first. If no matching megacategories are found, then level  2  megacategory tries are traversed, and so on until there are no more megacategory tries to traverse. When this procedure concludes, a set of megacategories remains that are matched to the current input.  
         [0062]    C. Determining an Appropriate Response Template  
         [0063]    Referring to FIGS. 7 and 8, process  80  determines ( 144 ) an appropriate response using a process  150 . Process  150  determines ( 154 ) if more than one megacategory matches. If more than one megacategory matches, process  150  determines ( 156 ) the highest “specificity rank” from each of the matching megacategories. The specificity rank is determined for each of the patterns during EAIL engine initialization in process  80  (see FIG. 4). The specificity rank of a megacategory is equal to the sum of the specificity ranks of the patterns that contributed to the matching of the megacategory. In the case of a tie, the megacategory with the highest single ranking for a specific pattern is used. Process  150  selects ( 158 ) the corresponding response template.  
         [0064]    Process  150  determines ( 160 ) if only one megacategory has been matched. If only one megacategory has been matched process  150  selects ( 158 ) the corresponding response template to the matched megacategory.  
         [0065]    Otherwise, no megacategories are matched. EAIL engine  10  stores a list of matched attributes for each user input. Process  150  retrieves ( 162 ) the matched attributes from the previous user input. Process  150  adds ( 164 ) the matched attributes from the previous input to a current list of matched attributes. Only matched attributes are propagated forward (i.e., topic variables and “that” tag variables do not propagate forward from previous inputs). After previous matched attributes are added to the current list, process  150  traverses ( 166 ) the tries for each level. Thus, EAIL engine  10  is “implicitly” determining context.  
         [0066]    For example, consider a knowledge base with the following data:  
                                                                       &lt;eail&gt;           &lt;attribute name=“head”&gt;           &lt;pattern&gt;* HEAD *&lt;/pattern&gt;           &lt;/attribute&gt;           &lt;attribute name=“pain”&gt;           &lt;pattern&gt;* HURT% *&lt;/pattern&gt;           &lt;/attribute&gt;           &lt;attribute name=“duration”&gt;           &lt;pattern&gt;WHEN * {START | BEGIN}&lt;/pattern&gt;           &lt;pattern&gt;HOW LONG *&lt;/pattern&gt;           &lt;/attribute&gt;           &lt;megacategory&gt;           &lt;expr&gt;head&lt;/expr&gt;           &lt;template&gt;My head hurts.&lt;/template&gt;           &lt;/megacategory&gt;           &lt;megacategory&gt;           &lt;expr&gt;head &amp;&amp; pain &amp;&amp; duration&lt;/expr&gt;           &lt;template&gt;My head has been hurting for about a                day&lt;/template&gt;                &lt;/megacategory&gt;           &lt;/eail&gt;                      
 
         [0067]    If the user types in, “Tell me about your head,” only the “head” variable will be set to true. The one megacategory with “head” as its expression will match, and EAIL engine  10  responds “My head hurts.” If the user types in, “How long has it been hurting,” the “pain” and “duration” variables will artificial both be set to true. However, there are no megacategories that match just those two variables. EAIL engine  10  adds “head,” from the last input, to the current list of matched attributes. The megacategory with “head &amp;&amp; pain &amp;&amp; duration” now matches, and EAIL engine  10  responds “My head has been hurting for about a day.” In this way, EAIL engine  10  determined that the user was talking about the head without the knowledge base code developer having to explicitly set a topic or a “that” tag.  
         [0068]    Process  150  determines ( 168 ) if there are any megacategories that match. If there are still no matching megacategories, process  150  disqualifies ( 170 ) the input. This ensures that EAIL engine  10  does not give the same response twice in a row when no matched attributes occur for a given input. Process  150  selects ( 172 ) a default response so that when executed responds to the user with a “request for clarification” response.  
         [0069]    If a pattern matches on the second traversal, process  150  saves ( 174 ) the attributes that match permanently to a list of “current” matched attributes. Thus, if the user asked another question about the “head”, as in the example described above, “head” would be a part of the previous list of matched attributes.  
         [0070]    Referring back to FIGS. 3 and 4, process  80  sends ( 144 ) the appropriate response. Process  60  determines ( 66 ) if there are additional inputs. If there are additional inputs, process  60  processes ( 64 ) the input.  
         [0071]    Other Processing Embodiments  
         [0072]    Processes  60 ,  80 ,  130  and  150  are not limited to use with the hardware and software of FIG. 1; it may find applicability in any computing or processing environment and with any type of machine that is capable of running a computer program. Processes  60 ,  80 ,  130  and  150  may be implemented in hardware, software, firmware or any combination of the three. For example, processes  60 ,  80 ,  130  and  150  may be implemented in a circuit that includes one or a combination of a processor, a memory, programmable logic and logic gates. Processes  60 ,  80 ,  130  and  150  may be implemented in computer programs executed on programmable computers/machines that each includes a processor, a storage medium or other article of manufacture that is readable by the processor (including volatile and non-volatile memory and/or storage elements), at least one input device, and one or more output devices. Program code may be applied to data entered using an input device to perform processes  60 ,  80 ,  130  and  150  and to generate output information.  
         [0073]    Each such program may be implemented in a high level procedural or object-oriented programming language to communicate with a computer system. However, the programs can be implemented in assembly or machine language. The language may be a compiled or an interpreted language. Each computer program may be stored on a storage medium or device (e.g., CD-ROM, hard disk, or magnetic diskette) that is readable by a general or special purpose programmable computer for configuring and operating the computer when the storage medium or device is read by the computer to perform processes  60 ,  80 ,  130  and  150 . Processes  60 ,  80 ,  130  and  150  may also be implemented as a machine-readable storage medium, configured with a computer program, where upon execution, instructions in the computer program cause the computer to operate in accordance with processes  60 ,  80 ,  130  and  150 .  
         [0074]    The process is not limited to the specific embodiments described herein. For example, GUI  20  does not need to display a three-dimensional person to depict the cyber personality. The dialogue between EAIL  10  and the user can be in the form of text messages on a screen. The process is not limited to the specific processing order of FIGS. 3, 4,  7  and  8 . Rather, the blocks of FIGS. 3, 4,  7  and  8  may be re-ordered, as necessary, to achieve the results set forth above.  
         [0075]    Other embodiments not described herein are also within the scope of the following claims.