# Research on Collaborative Interaction Model of Knowledge Sharing in Industry-University Cooperation

Authors: Jing Li
Journal: Wireless Communications and Mobile Computing
 (2022)

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## Abstract

Knowledge sharing between the enterprises and universities, across the field of economy and science education, may bring many differences that may lead to conflicts of all kinds in the process of cooperation. How to improve the performance of knowledge sharing in industry-university cooperation has become an urgent problem to be solved. Based on knowledge management, using qualitative and quantitative analysis, literature search, normative analysis, and academic surveys, the thesis has made a series of studies on the key factors which companies and universities are faced with in improving knowledge sharing performance. The paper takes knowledge sharing in industry-university cooperation as an organic system composed of four elements which are subject elements, object elements, media elements and environmental elements. On this basis, it gives an analysis about the whole working process of these elements and builds a compound cooperating and interactive model in industry-university cooperation and knowledge sharing based on role-playing to illustrate the process and the purpose. With the shorter and shorter transformation cycle between technology and productivity, the process of knowledge sharing in industry-university cooperation is often a complex collaborative process of multiple dynamic, repeated operations and spiral rise.


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## Body

## 1. Introduction

The element structure of knowledge sharing in industry-university cooperation conforms to the coupling law of self-organization and collaboration, that is, the internal connection law established by different types of element structures in a certain time and space according to the temporal relationship and quantitative proportion. In the process of knowledge sharing in industry-university cooperation, explicit knowledge and tacit knowledge, applied knowledge and basic knowledge, self-owned knowledge and common knowledge, personal knowledge, and organizational knowledge flow and share between enterprises and universities.Combined with the domestic and foreign literature analyzed above and the mechanism of knowledge sharing of industry-university cooperation, two factors of internal knowledge transformation and external knowledge transformation must be considered in constructing the operation model of elements of knowledge sharing of industry-university cooperation [1]. From the inside and outside of the organization, the knowledge sharing between industry and university has the overflow of its own knowledge and the integration, absorption, and application of common knowledge at the three levels of individual, department, and organization. At the individual level, it emphasizes individual communication and communication based on tacit knowledge and pays attention to real-time interaction. All member organizations attach great importance to knowledge exchange and sharing at this level and are very cautious in the operation process; at the departmental and organizational levels, it emphasizes the dissemination and sharing of collective knowledge based on explicit knowledge and pays attention to asynchronous knowledge exchange and sharing.


## 2. Overall Operation Model of Knowledge Sharing in Industry-University Cooperation

The knowledge sharing of industry-university cooperation is much more complex and difficult than that within a single organization. We can build an overall operation model of knowledge sharing elements of industry-university cooperation, as shown in Figure1. In the knowledge sharing of industry-university cooperation, tacit knowledge and explicit knowledge, basic knowledge and applied knowledge, self-owned knowledge and common knowledge, personal knowledge, and organizational knowledge interact and complement each other and form a growing knowledge spiral synergy model through circular transformation. The three processes of knowledge sharing in industry-university cooperation are as follows: first, the process of self-owned knowledge selection and spillover; second, the integration of knowledge and the formation process of common knowledge; third, the absorption and application process of common knowledge. All kinds of knowledge operate in the two directions of epistemological dimension and ontological dimension and interact with each other. This two-way flow of knowledge is carried out among organizations and individuals in the organization. It is a socially interactive process, which promotes the two-way crossover sharing of innovation ability between industry and university.Figure 1
Overall operation model of knowledge sharing in industry-university cooperation.Industry-university cooperation knowledge sharing is a dynamic two-way knowledge flow process including the interaction, interaction, and mutual choice of innovation participants such as enterprises and universities. It is a decision-making process of public choice. In order to realize effective knowledge sharing, industry-university cooperation actually contains two basic assumptions: one is a perfect market economic system and mechanism, technology, talent, information, capital, and other resources have a relatively perfect market, and enterprises, universities, and other organizations perform their duties and show their abilities; the second is knowledge sharing. Both parties take what they need and do their best. The key is that enterprises and universities must have the ability to absorb, digest, and reinnovate knowledge. Leaving these assumptions to talk about industry-university cooperation knowledge sharing not only has little practical significance and also the implementation effect is greatly reduced. For a long time, the functional and structural imbalance of China’s innovation resources, innovation ability, and information distribution is the key to hindering the improvement of China’s innovation ability. Structural imbalance is the basic internal factor restricting the development of China’s national innovation system, and functional imbalance further amplifies this restriction. The most direct consequence of the interaction of the two imbalances is the absence of an innovation interface between enterprises and universities. This absence and dislocation reduces the allocation efficiency of China’s scientific and technological resources and hinders the cultivation and development of the national innovation system [2]. It is undeniable that university technology transfer alleviates this imbalance to a certain extent, but it does not fundamentally solve the imbalance.Therefore, we must actively promote the sharing of innovation ability under the guidance of system thought and system theory and in combination with the actual situation of knowledge sharing between enterprises and universities in China, so as to fundamentally solve the problem of “failure” of industry-university cooperation [3]. The so-called innovation capability sharing is based on the nonlinear, dynamic, and diversified concept of innovation, guided by the system theory, organizational behavior theory, innovation management theory, and technical economics theory, with the purpose of optimizing the allocation of innovation resources, realizing the organic combination of science and technology and economy, and improving the knowledge innovation capability of enterprises and universities The resource sharing mechanism, innovation network mechanism, and interactive learning mechanism are the dynamic process of two-way flow between enterprises and universities in a step-by-step, phased, and all-round way.The impact of universities on enterprise innovation ability is mainly reflected in the following aspects: first, the ability to collect, sort, and package knowledge. The initial state of knowledge is scattered and disordered. Only through knowledge integration can knowledge dissemination be carried out. Secondly, tacit knowledge is explicit. Tacit knowledge can only be used by most people after being explicit. A considerable part of the research results of university scholars is the result of explicit tacit knowledge. The explicit skills of tacit knowledge itself are also a very important innovation ability. Third, we provide knowledge analysis services for enterprises. The knowledge service center of the university can act as a bystander to diagnose the knowledge of enterprises, analyze the knowledge structure of enterprises, find the “short board” of enterprise knowledge, and help group enterprises improve the knowledge structure. Finally, we promote the speed of knowledge transfer. If knowledge is used by human beings one day earlier, it can create value for human beings one day earlier. Therefore, the transmission speed of knowledge in society will directly affect the value it creates for society [4].The influence of enterprises on the innovation ability of universities is as follows: First, it affects the teaching process of universities. In higher education, knowledge is linked with “learning,” textbooks are the model of knowledge, the dissemination process of knowledge is “learning,” and “learning” is a one-way process. The results of learning are measured by “right” and “wrong” with reference to certain standards. Therefore, in this mechanism, knowledge is still recognized as “inherited knowledge” and true rational knowledge. It is still traditional static knowledge. Through the transmission of enterprise innovation ability, the university teaching process will become a kind of dynamic knowledge transmission. Secondly, it helps universities meet the challenge of knowledge integration. Under the condition that cross research has become an important driving source of knowledge innovation, the traditional discipline classification leads to interdisciplinary barriers, which seriously affects the efficiency and benefit of knowledge production in schools, and increasingly becomes an obstacle to knowledge innovation. Therefore, learning from enterprise technological innovation capability will help universities break discipline boundaries, create an environment for mutual communication, and strive to start integration. Finally, it helps the diffusion of university knowledge in society. The traditional role of the university is to cultivate talents. As a talent base, the university undertakes more the function of disseminating knowledge to the social elite. Due to the characteristics of the university organization, the knowledge production and dissemination activities of the university are still separated from the knowledge application activities of the society, and its social transmission function of knowledge cannot be well utilized. Enterprises can well help universities carry out the function of social integration through knowledge trading and achievement transformation with universities [5].


## 3. Subject Synergy and Interaction of Industry-University Cooperation and Knowledge Sharing

### 3.1. Concept of Subject Collaboration and Interaction in Knowledge Sharing of Industry-University Cooperation

#### 3.1.1. Concept of Agent Collaborative Interaction

The cooperative interaction behavior between subjects is not only an important manifestation of the subject’s sociality but also an important attribute of the subject different from the traditional organization system. A rational and perfect cooperative interaction mechanism is the basis for coordination, cooperation, and negotiation among multiple subjects, but also the premise to reflect the organizational relationship between various subject roles in the subject organization. Here, it is necessary to further explain the concept of collaborative interaction.Carayanni et al. [6] analyzed the social synergy from the space-time dimension and divided the social synergy into horizontal and vertical synergy modes. Horizontal collaboration is the oldest and simplest collaboration scheme, which refers to the collaborative behavior of multiple individuals to complete a project. Through this collaboration, people can complete a large-scale project that one person cannot complete or divide and complete each part of a project by multiple people, so as to simplify the work complexity and increase its work efficiency. Vertical collaboration refers to the phenomenon that the results of one research or project can assist or actually help to complete another project in the future. From the way of social synergy, the phenomenon of social synergy can be divided into two modes: one-way and two-way. Unidirectional collaboration refers to collaborative activities carried out only for the purpose of one of the collaborative participants. Unidirectional collaboration has two parts: the collaborator and the cooperate. The collaboration mode is the planning and beneficiary of collaboration, and the cooperate is the executor relative to the collaborator. Two-way collaboration refers to the collaborative activities carried out by some or all participants to benefit themselves. This is the most common way for human beings. Industry-university cooperation and knowledge sharing belong to this form.Synergetic pointed out that in the interaction process of various elements within the system, one is the parameter that determines the order degree of the system, that is, the main contradiction or the main aspect of the contradiction that determines the state of things. At the same time, research also points out that this order parameter is the subsystem with the slowest evolution speed in the system; that is, the slow variable determines the evolution process of the system and the structure and function of the evolution result. In the system, the fast variable is subject to the slow variable, and the fast variable is dominated by the slow variable. “Order parameter” promotes the combination of different elements to evolve and develop by themselves, and leads the system to a higher and orderly structure. For the knowledge sharing of industry-university cooperation, collaborative interaction is to form an order parameter through the interaction between enterprise knowledge subject and university knowledge subject, which determines the main development direction of industry-university cooperation. This collaborative interaction is actually the result of the integration of complementary knowledge resources between enterprises and universities, resulting in a collaborative advantage of 1 + 1 > 2.Firstly, strictly speaking, the knowledge collaborative interaction behavior between production and learning subjects is still a way of interaction between subjects and the external environment, but due to its special interaction object and significance, it is very necessary to study it separately.Secondly, from the perspective of subject organization, the purpose of subject collaborative interaction is closely related to its corresponding role objectives. Therefore, strictly speaking, the interaction objects involved in the process of collaborative interaction appear as roles. In particular, the interaction protocol and interaction strategy between agents are actually the interaction protocol and interaction strategy between agent roles. In addition, the interaction here is a relatively broad concept, which generally refers to the communication behavior in the form of knowledge sharing between the subjects of industry-university cooperation. In this way, any communication, cooperation, negotiation, or arbitration between the subjects of industry-university cooperation and knowledge sharing belong to this category.The interaction of subjects is the characterization of the internal factors of the interaction behavior of subjects. Taking human social organization as a reference, we will find that the interaction of any rational entity must involve the purpose, object, and mode of interaction. Therefore, as the abstraction of rational entity, the research on subject interaction should also start from how to solve these three problems, namely, first, why interaction? Second, with whom? Third, how to interact? The first and second questions involve the generation of subject interaction motivation and reasoning in the process of interaction. We will explain it by analyzing the changes of subject thinking state of knowledge sharing in industry-university cooperation; the third problem involves the implementation of the whole interaction. Based on the analysis of the element structure of knowledge sharing in industry-university cooperation, we will put forward the subject interaction hierarchical model and, through the analysis of the model, give the framework of the subject interaction mechanism of knowledge sharing in industry-university cooperation.


#### 3.1.2. Thinking Basis of Subject’s Cooperative Interaction Behavior

First of all, it should be clear that the knowledge exchange in the interaction process of the knowledge-sharing subject of industry-university cooperation is also an action, because the subject, as a rational conscious entity, and its interaction behavior, like other behaviors, are driven by a certain goal, combine the internal thinking state with the external environment, and are determined through certain thinking and reasoning.At the same time, based on different interaction levels, this action may also be an action sequence or some kind of protocol. From the perspective of choice and decision-making, their thinking process is consistent, which is simply called action here.According to the semantic model of FIPA communication behavior and Cohen and Levesque’s intention theory [7], this paper briefly describes the thinking process of subject interaction behavior.Firstly, some basic symbol definitions are given, as shown in Table1.Table 1
Basic symbol definitions.
SymbolDefinitionP, P1, P2Different propositional formulasag, ag1, ag2Different subject individualsa, a1, a2Different actions (or events corresponding to actions)a1; a2The action sequence,a1 first and a2 latera1|a2Nondeterministic action selection; ora1 or a2, but not at the same time∼pMeansP is trueBel (agi,p)Indicates that agi believes thatp is trueCan (agi,a)Indicates that agi is capable of performing action aInt (agi,p)Indicates that agi expectsp to be trueFeasible (a, p)Indicates that a may occur in the future, andP is true after a occursDone (a, P)Means that a just happened, andP is true before a happenedIn the simplified case, we define the thinking state of the knowledge sharing subject of industry-university cooperation as three independent elements:①
Belief: belief is used to express the subject’s information attitude. If a belief is true, it means that the subject accepts the corresponding proposition as true; accepting a false proposition means accepting whether the proposition is true or not.②
Ability: ability is used to represent the background of the subject performing an action. If a certain ability is true, it means that the subject has the ability to perform corresponding actions; otherwise, it is false.③
Intention: intention indicates a choice, that is, the state in which the subject expects to be true but does not believe to be true at present. The determination of intention will directly lead to the corresponding action selection.The three concepts of belief, ability and intention are represented by operators bel, can, and int, respectively, and are recorded as shown in Table1. In order to express the time relationship in the reasoning process, the operators related to time sequence are defined in Table 1:For simplicity, note:Feasible (a) ≡ Feasible (a, True)Done (a) ≡ Done (a, True)Possible (p) ≡ (a) Feasible (a, p)Because the occurrence of each action must meet certain conditions, and at the same time, the occurrence of the action is bound to produce corresponding results, it is possible to define the probability preconditions and rational effects of action a as FP (a) and re (a), respectively.Obviously, for any rational subject, the re (a) of action a should be consistent with the intention of implementing the action; the satisfaction of FP (a) is the premise for the implementation of action a. Therefore, it has the following properties.Property 1.
∼int (AGI, P) ⟶ int (AGI, done (A1…|an)), where for AK, K ∈ [1, …, n], there is (x) bel (AGI, AK = x), and re (AK) = p; and int (AGI, possible (done (AK))).Property 2.
∼int (AGI, done (a)) ⟶ int (agj, re (a)).Property 3.
∼int (AGI, done (a)) ⟶ (can (AGI, a) ∨ (agj) can (agj, a))
Among them, Property1 shows that the intention of the subject will be transformed into certain actions, which meet the following conditions: First, the action is understood by the subject. Second, the result of the action corresponds to the intention of the subject. Third, the subject has no reason not to implement the action. Property 2 describes the intention premise of expecting an action to occur. Property 3 describes the ability premise implied by the expectation of an action.
With the support of these three properties, the interactive behavior between the subjects of knowledge sharing in industry-university cooperation can be expressed by logical derivation.
Firstly, using the semantic model of FIPA communication behavior, an action can be recorded as:<agi, act-name (agj,C)>FP:p1RE:p2
Here, act-name represents the action name, agi is the initiator of the action, agj is the recipient of the action,C represents the action content, and FP and RE represent the antecedents and consequences of the action, respectively. (implication: in the judgment of sufficient condition hypothesis: if P, then q can be expressed as P ⟶ Q, P is called the antecedent (condition), q is called the consequent (consequence), the symbol “⟶”, and logic is called “implication”).
The following is a simple example to describe the thinking process of the subject implementing a certain action of knowledge sharing in industry-university cooperation. Firstly, the expressions of several actions are given:①
Act1FP: p-fp1RE: p-re1②
<agi, request (agj,a)>FP: Can (agi,a) ∧ Can (agj, a)RE: Done (a)Suppose there is AG1 a person whose thinking state is:Int (ag1, p-re1)∧ Bel (ag1, p-re1) ∧ Bel (ag1, Can (ag1, act1)) ∧ Bel (ag1, Can (ag2, act1)) ∧ Bel (ag1, Can (ag1, < ag1, request (ag2, a)>))
Therefore, according to Property1, int (AG1, done (act1)) can be deduced from int (AG1, p-re1). Obviously, the intention satisfies Properties 2 and 3, but because bel (AG1, can (AG1, act1)), there is int (AG1, done (<AG1, request (ag2, act1)>) according to Property 1. Obviously, the intention satisfies Properties 2 and 3. At the same time, there is bel (AG1, can (AG1, <AG1, request (ag2, a)>), so AG1 selects the action <AG1, request (ag2, act1)>. In essence, the thinking basis of the interaction behavior of the knowledge-sharing subject of industry-university cooperation is still the rational principle.


### 3.2. Subject Collaboration and Interaction Process of Knowledge Sharing in Industry-University Cooperation

The collaborative interaction of knowledge sharing in industry-university cooperation is often based on a project. Through collaborative interaction, new knowledge can be generated and quickly transformed into enterprise technical capability and university scientific research and talent training advantages. The collaborative interaction process of knowledge sharing in industry-university cooperation is shown in Figure2 [8]. From this model framework, we can see that the collaborative interaction process of industry-university cooperation knowledge sharing can be divided into the following three stages [9]. The structural framework of the subject can be used to support the subject to combine its own behavior ability with the planning ability of the corresponding role, so as to ensure the realization of the role goal.Figure 2
Knowledge-sharing and collaborative interaction process of industry-university cooperation.The knowledge sharing of industry-university cooperation is completed by different subjects. The subject organization theory constructed by Wu Sheng [10] holds that the external functional performance of any entity in the real environment is always determined by its internal structural characteristics. The internal structure of the subject is also closely related to its functional characteristics. Different environments, different application purposes, and different implementation methods make the subjects show differences in many aspects. Industry-university cooperative knowledge sharing is a cooperative relationship formed by two different types of subjects, enterprises and universities, in order to achieve a common cooperative innovation goal. It is a process of collaborative production of new knowledge between enterprises and universities.The collaborative interaction of knowledge sharing in industry-university cooperation is often based on a project. Through collaborative interaction, new knowledge can be generated and quickly transformed into enterprise technical capability and university scientific research and talent training advantages. The collaborative interaction process of knowledge sharing in industry-university cooperation is shown in Figure2. From this model framework, we can see that the collaborative interaction process of industry-university cooperation knowledge sharing can be divided into the following three stages.


## 3.1. Concept of Subject Collaboration and Interaction in Knowledge Sharing of Industry-University Cooperation

### 3.1.1. Concept of Agent Collaborative Interaction

The cooperative interaction behavior between subjects is not only an important manifestation of the subject’s sociality but also an important attribute of the subject different from the traditional organization system. A rational and perfect cooperative interaction mechanism is the basis for coordination, cooperation, and negotiation among multiple subjects, but also the premise to reflect the organizational relationship between various subject roles in the subject organization. Here, it is necessary to further explain the concept of collaborative interaction.Carayanni et al. [6] analyzed the social synergy from the space-time dimension and divided the social synergy into horizontal and vertical synergy modes. Horizontal collaboration is the oldest and simplest collaboration scheme, which refers to the collaborative behavior of multiple individuals to complete a project. Through this collaboration, people can complete a large-scale project that one person cannot complete or divide and complete each part of a project by multiple people, so as to simplify the work complexity and increase its work efficiency. Vertical collaboration refers to the phenomenon that the results of one research or project can assist or actually help to complete another project in the future. From the way of social synergy, the phenomenon of social synergy can be divided into two modes: one-way and two-way. Unidirectional collaboration refers to collaborative activities carried out only for the purpose of one of the collaborative participants. Unidirectional collaboration has two parts: the collaborator and the cooperate. The collaboration mode is the planning and beneficiary of collaboration, and the cooperate is the executor relative to the collaborator. Two-way collaboration refers to the collaborative activities carried out by some or all participants to benefit themselves. This is the most common way for human beings. Industry-university cooperation and knowledge sharing belong to this form.Synergetic pointed out that in the interaction process of various elements within the system, one is the parameter that determines the order degree of the system, that is, the main contradiction or the main aspect of the contradiction that determines the state of things. At the same time, research also points out that this order parameter is the subsystem with the slowest evolution speed in the system; that is, the slow variable determines the evolution process of the system and the structure and function of the evolution result. In the system, the fast variable is subject to the slow variable, and the fast variable is dominated by the slow variable. “Order parameter” promotes the combination of different elements to evolve and develop by themselves, and leads the system to a higher and orderly structure. For the knowledge sharing of industry-university cooperation, collaborative interaction is to form an order parameter through the interaction between enterprise knowledge subject and university knowledge subject, which determines the main development direction of industry-university cooperation. This collaborative interaction is actually the result of the integration of complementary knowledge resources between enterprises and universities, resulting in a collaborative advantage of 1 + 1 > 2.Firstly, strictly speaking, the knowledge collaborative interaction behavior between production and learning subjects is still a way of interaction between subjects and the external environment, but due to its special interaction object and significance, it is very necessary to study it separately.Secondly, from the perspective of subject organization, the purpose of subject collaborative interaction is closely related to its corresponding role objectives. Therefore, strictly speaking, the interaction objects involved in the process of collaborative interaction appear as roles. In particular, the interaction protocol and interaction strategy between agents are actually the interaction protocol and interaction strategy between agent roles. In addition, the interaction here is a relatively broad concept, which generally refers to the communication behavior in the form of knowledge sharing between the subjects of industry-university cooperation. In this way, any communication, cooperation, negotiation, or arbitration between the subjects of industry-university cooperation and knowledge sharing belong to this category.The interaction of subjects is the characterization of the internal factors of the interaction behavior of subjects. Taking human social organization as a reference, we will find that the interaction of any rational entity must involve the purpose, object, and mode of interaction. Therefore, as the abstraction of rational entity, the research on subject interaction should also start from how to solve these three problems, namely, first, why interaction? Second, with whom? Third, how to interact? The first and second questions involve the generation of subject interaction motivation and reasoning in the process of interaction. We will explain it by analyzing the changes of subject thinking state of knowledge sharing in industry-university cooperation; the third problem involves the implementation of the whole interaction. Based on the analysis of the element structure of knowledge sharing in industry-university cooperation, we will put forward the subject interaction hierarchical model and, through the analysis of the model, give the framework of the subject interaction mechanism of knowledge sharing in industry-university cooperation.


### 3.1.2. Thinking Basis of Subject’s Cooperative Interaction Behavior

First of all, it should be clear that the knowledge exchange in the interaction process of the knowledge-sharing subject of industry-university cooperation is also an action, because the subject, as a rational conscious entity, and its interaction behavior, like other behaviors, are driven by a certain goal, combine the internal thinking state with the external environment, and are determined through certain thinking and reasoning.At the same time, based on different interaction levels, this action may also be an action sequence or some kind of protocol. From the perspective of choice and decision-making, their thinking process is consistent, which is simply called action here.According to the semantic model of FIPA communication behavior and Cohen and Levesque’s intention theory [7], this paper briefly describes the thinking process of subject interaction behavior.Firstly, some basic symbol definitions are given, as shown in Table1.Table 1
Basic symbol definitions.
SymbolDefinitionP, P1, P2Different propositional formulasag, ag1, ag2Different subject individualsa, a1, a2Different actions (or events corresponding to actions)a1; a2The action sequence,a1 first and a2 latera1|a2Nondeterministic action selection; ora1 or a2, but not at the same time∼pMeansP is trueBel (agi,p)Indicates that agi believes thatp is trueCan (agi,a)Indicates that agi is capable of performing action aInt (agi,p)Indicates that agi expectsp to be trueFeasible (a, p)Indicates that a may occur in the future, andP is true after a occursDone (a, P)Means that a just happened, andP is true before a happenedIn the simplified case, we define the thinking state of the knowledge sharing subject of industry-university cooperation as three independent elements:①
Belief: belief is used to express the subject’s information attitude. If a belief is true, it means that the subject accepts the corresponding proposition as true; accepting a false proposition means accepting whether the proposition is true or not.②
Ability: ability is used to represent the background of the subject performing an action. If a certain ability is true, it means that the subject has the ability to perform corresponding actions; otherwise, it is false.③
Intention: intention indicates a choice, that is, the state in which the subject expects to be true but does not believe to be true at present. The determination of intention will directly lead to the corresponding action selection.The three concepts of belief, ability and intention are represented by operators bel, can, and int, respectively, and are recorded as shown in Table1. In order to express the time relationship in the reasoning process, the operators related to time sequence are defined in Table 1:For simplicity, note:Feasible (a) ≡ Feasible (a, True)Done (a) ≡ Done (a, True)Possible (p) ≡ (a) Feasible (a, p)Because the occurrence of each action must meet certain conditions, and at the same time, the occurrence of the action is bound to produce corresponding results, it is possible to define the probability preconditions and rational effects of action a as FP (a) and re (a), respectively.Obviously, for any rational subject, the re (a) of action a should be consistent with the intention of implementing the action; the satisfaction of FP (a) is the premise for the implementation of action a. Therefore, it has the following properties.Property 1.
∼int (AGI, P) ⟶ int (AGI, done (A1…|an)), where for AK, K ∈ [1, …, n], there is (x) bel (AGI, AK = x), and re (AK) = p; and int (AGI, possible (done (AK))).Property 2.
∼int (AGI, done (a)) ⟶ int (agj, re (a)).Property 3.
∼int (AGI, done (a)) ⟶ (can (AGI, a) ∨ (agj) can (agj, a))
Among them, Property1 shows that the intention of the subject will be transformed into certain actions, which meet the following conditions: First, the action is understood by the subject. Second, the result of the action corresponds to the intention of the subject. Third, the subject has no reason not to implement the action. Property 2 describes the intention premise of expecting an action to occur. Property 3 describes the ability premise implied by the expectation of an action.
With the support of these three properties, the interactive behavior between the subjects of knowledge sharing in industry-university cooperation can be expressed by logical derivation.
Firstly, using the semantic model of FIPA communication behavior, an action can be recorded as:<agi, act-name (agj,C)>FP:p1RE:p2
Here, act-name represents the action name, agi is the initiator of the action, agj is the recipient of the action,C represents the action content, and FP and RE represent the antecedents and consequences of the action, respectively. (implication: in the judgment of sufficient condition hypothesis: if P, then q can be expressed as P ⟶ Q, P is called the antecedent (condition), q is called the consequent (consequence), the symbol “⟶”, and logic is called “implication”).
The following is a simple example to describe the thinking process of the subject implementing a certain action of knowledge sharing in industry-university cooperation. Firstly, the expressions of several actions are given:①
Act1FP: p-fp1RE: p-re1②
<agi, request (agj,a)>FP: Can (agi,a) ∧ Can (agj, a)RE: Done (a)Suppose there is AG1 a person whose thinking state is:Int (ag1, p-re1)∧ Bel (ag1, p-re1) ∧ Bel (ag1, Can (ag1, act1)) ∧ Bel (ag1, Can (ag2, act1)) ∧ Bel (ag1, Can (ag1, < ag1, request (ag2, a)>))
Therefore, according to Property1, int (AG1, done (act1)) can be deduced from int (AG1, p-re1). Obviously, the intention satisfies Properties 2 and 3, but because bel (AG1, can (AG1, act1)), there is int (AG1, done (<AG1, request (ag2, act1)>) according to Property 1. Obviously, the intention satisfies Properties 2 and 3. At the same time, there is bel (AG1, can (AG1, <AG1, request (ag2, a)>), so AG1 selects the action <AG1, request (ag2, act1)>. In essence, the thinking basis of the interaction behavior of the knowledge-sharing subject of industry-university cooperation is still the rational principle.


## 3.1.1. Concept of Agent Collaborative Interaction

The cooperative interaction behavior between subjects is not only an important manifestation of the subject’s sociality but also an important attribute of the subject different from the traditional organization system. A rational and perfect cooperative interaction mechanism is the basis for coordination, cooperation, and negotiation among multiple subjects, but also the premise to reflect the organizational relationship between various subject roles in the subject organization. Here, it is necessary to further explain the concept of collaborative interaction.Carayanni et al. [6] analyzed the social synergy from the space-time dimension and divided the social synergy into horizontal and vertical synergy modes. Horizontal collaboration is the oldest and simplest collaboration scheme, which refers to the collaborative behavior of multiple individuals to complete a project. Through this collaboration, people can complete a large-scale project that one person cannot complete or divide and complete each part of a project by multiple people, so as to simplify the work complexity and increase its work efficiency. Vertical collaboration refers to the phenomenon that the results of one research or project can assist or actually help to complete another project in the future. From the way of social synergy, the phenomenon of social synergy can be divided into two modes: one-way and two-way. Unidirectional collaboration refers to collaborative activities carried out only for the purpose of one of the collaborative participants. Unidirectional collaboration has two parts: the collaborator and the cooperate. The collaboration mode is the planning and beneficiary of collaboration, and the cooperate is the executor relative to the collaborator. Two-way collaboration refers to the collaborative activities carried out by some or all participants to benefit themselves. This is the most common way for human beings. Industry-university cooperation and knowledge sharing belong to this form.Synergetic pointed out that in the interaction process of various elements within the system, one is the parameter that determines the order degree of the system, that is, the main contradiction or the main aspect of the contradiction that determines the state of things. At the same time, research also points out that this order parameter is the subsystem with the slowest evolution speed in the system; that is, the slow variable determines the evolution process of the system and the structure and function of the evolution result. In the system, the fast variable is subject to the slow variable, and the fast variable is dominated by the slow variable. “Order parameter” promotes the combination of different elements to evolve and develop by themselves, and leads the system to a higher and orderly structure. For the knowledge sharing of industry-university cooperation, collaborative interaction is to form an order parameter through the interaction between enterprise knowledge subject and university knowledge subject, which determines the main development direction of industry-university cooperation. This collaborative interaction is actually the result of the integration of complementary knowledge resources between enterprises and universities, resulting in a collaborative advantage of 1 + 1 > 2.Firstly, strictly speaking, the knowledge collaborative interaction behavior between production and learning subjects is still a way of interaction between subjects and the external environment, but due to its special interaction object and significance, it is very necessary to study it separately.Secondly, from the perspective of subject organization, the purpose of subject collaborative interaction is closely related to its corresponding role objectives. Therefore, strictly speaking, the interaction objects involved in the process of collaborative interaction appear as roles. In particular, the interaction protocol and interaction strategy between agents are actually the interaction protocol and interaction strategy between agent roles. In addition, the interaction here is a relatively broad concept, which generally refers to the communication behavior in the form of knowledge sharing between the subjects of industry-university cooperation. In this way, any communication, cooperation, negotiation, or arbitration between the subjects of industry-university cooperation and knowledge sharing belong to this category.The interaction of subjects is the characterization of the internal factors of the interaction behavior of subjects. Taking human social organization as a reference, we will find that the interaction of any rational entity must involve the purpose, object, and mode of interaction. Therefore, as the abstraction of rational entity, the research on subject interaction should also start from how to solve these three problems, namely, first, why interaction? Second, with whom? Third, how to interact? The first and second questions involve the generation of subject interaction motivation and reasoning in the process of interaction. We will explain it by analyzing the changes of subject thinking state of knowledge sharing in industry-university cooperation; the third problem involves the implementation of the whole interaction. Based on the analysis of the element structure of knowledge sharing in industry-university cooperation, we will put forward the subject interaction hierarchical model and, through the analysis of the model, give the framework of the subject interaction mechanism of knowledge sharing in industry-university cooperation.


## 3.1.2. Thinking Basis of Subject’s Cooperative Interaction Behavior

First of all, it should be clear that the knowledge exchange in the interaction process of the knowledge-sharing subject of industry-university cooperation is also an action, because the subject, as a rational conscious entity, and its interaction behavior, like other behaviors, are driven by a certain goal, combine the internal thinking state with the external environment, and are determined through certain thinking and reasoning.At the same time, based on different interaction levels, this action may also be an action sequence or some kind of protocol. From the perspective of choice and decision-making, their thinking process is consistent, which is simply called action here.According to the semantic model of FIPA communication behavior and Cohen and Levesque’s intention theory [7], this paper briefly describes the thinking process of subject interaction behavior.Firstly, some basic symbol definitions are given, as shown in Table1.Table 1
Basic symbol definitions.
SymbolDefinitionP, P1, P2Different propositional formulasag, ag1, ag2Different subject individualsa, a1, a2Different actions (or events corresponding to actions)a1; a2The action sequence,a1 first and a2 latera1|a2Nondeterministic action selection; ora1 or a2, but not at the same time∼pMeansP is trueBel (agi,p)Indicates that agi believes thatp is trueCan (agi,a)Indicates that agi is capable of performing action aInt (agi,p)Indicates that agi expectsp to be trueFeasible (a, p)Indicates that a may occur in the future, andP is true after a occursDone (a, P)Means that a just happened, andP is true before a happenedIn the simplified case, we define the thinking state of the knowledge sharing subject of industry-university cooperation as three independent elements:①
Belief: belief is used to express the subject’s information attitude. If a belief is true, it means that the subject accepts the corresponding proposition as true; accepting a false proposition means accepting whether the proposition is true or not.②
Ability: ability is used to represent the background of the subject performing an action. If a certain ability is true, it means that the subject has the ability to perform corresponding actions; otherwise, it is false.③
Intention: intention indicates a choice, that is, the state in which the subject expects to be true but does not believe to be true at present. The determination of intention will directly lead to the corresponding action selection.The three concepts of belief, ability and intention are represented by operators bel, can, and int, respectively, and are recorded as shown in Table1. In order to express the time relationship in the reasoning process, the operators related to time sequence are defined in Table 1:For simplicity, note:Feasible (a) ≡ Feasible (a, True)Done (a) ≡ Done (a, True)Possible (p) ≡ (a) Feasible (a, p)Because the occurrence of each action must meet certain conditions, and at the same time, the occurrence of the action is bound to produce corresponding results, it is possible to define the probability preconditions and rational effects of action a as FP (a) and re (a), respectively.Obviously, for any rational subject, the re (a) of action a should be consistent with the intention of implementing the action; the satisfaction of FP (a) is the premise for the implementation of action a. Therefore, it has the following properties.Property 1.
∼int (AGI, P) ⟶ int (AGI, done (A1…|an)), where for AK, K ∈ [1, …, n], there is (x) bel (AGI, AK = x), and re (AK) = p; and int (AGI, possible (done (AK))).Property 2.
∼int (AGI, done (a)) ⟶ int (agj, re (a)).Property 3.
∼int (AGI, done (a)) ⟶ (can (AGI, a) ∨ (agj) can (agj, a))
Among them, Property1 shows that the intention of the subject will be transformed into certain actions, which meet the following conditions: First, the action is understood by the subject. Second, the result of the action corresponds to the intention of the subject. Third, the subject has no reason not to implement the action. Property 2 describes the intention premise of expecting an action to occur. Property 3 describes the ability premise implied by the expectation of an action.
With the support of these three properties, the interactive behavior between the subjects of knowledge sharing in industry-university cooperation can be expressed by logical derivation.
Firstly, using the semantic model of FIPA communication behavior, an action can be recorded as:<agi, act-name (agj,C)>FP:p1RE:p2
Here, act-name represents the action name, agi is the initiator of the action, agj is the recipient of the action,C represents the action content, and FP and RE represent the antecedents and consequences of the action, respectively. (implication: in the judgment of sufficient condition hypothesis: if P, then q can be expressed as P ⟶ Q, P is called the antecedent (condition), q is called the consequent (consequence), the symbol “⟶”, and logic is called “implication”).
The following is a simple example to describe the thinking process of the subject implementing a certain action of knowledge sharing in industry-university cooperation. Firstly, the expressions of several actions are given:①
Act1FP: p-fp1RE: p-re1②
<agi, request (agj,a)>FP: Can (agi,a) ∧ Can (agj, a)RE: Done (a)Suppose there is AG1 a person whose thinking state is:Int (ag1, p-re1)∧ Bel (ag1, p-re1) ∧ Bel (ag1, Can (ag1, act1)) ∧ Bel (ag1, Can (ag2, act1)) ∧ Bel (ag1, Can (ag1, < ag1, request (ag2, a)>))
Therefore, according to Property1, int (AG1, done (act1)) can be deduced from int (AG1, p-re1). Obviously, the intention satisfies Properties 2 and 3, but because bel (AG1, can (AG1, act1)), there is int (AG1, done (<AG1, request (ag2, act1)>) according to Property 1. Obviously, the intention satisfies Properties 2 and 3. At the same time, there is bel (AG1, can (AG1, <AG1, request (ag2, a)>), so AG1 selects the action <AG1, request (ag2, act1)>. In essence, the thinking basis of the interaction behavior of the knowledge-sharing subject of industry-university cooperation is still the rational principle.


## 3.2. Subject Collaboration and Interaction Process of Knowledge Sharing in Industry-University Cooperation

The collaborative interaction of knowledge sharing in industry-university cooperation is often based on a project. Through collaborative interaction, new knowledge can be generated and quickly transformed into enterprise technical capability and university scientific research and talent training advantages. The collaborative interaction process of knowledge sharing in industry-university cooperation is shown in Figure2 [8]. From this model framework, we can see that the collaborative interaction process of industry-university cooperation knowledge sharing can be divided into the following three stages [9]. The structural framework of the subject can be used to support the subject to combine its own behavior ability with the planning ability of the corresponding role, so as to ensure the realization of the role goal.Figure 2
Knowledge-sharing and collaborative interaction process of industry-university cooperation.The knowledge sharing of industry-university cooperation is completed by different subjects. The subject organization theory constructed by Wu Sheng [10] holds that the external functional performance of any entity in the real environment is always determined by its internal structural characteristics. The internal structure of the subject is also closely related to its functional characteristics. Different environments, different application purposes, and different implementation methods make the subjects show differences in many aspects. Industry-university cooperative knowledge sharing is a cooperative relationship formed by two different types of subjects, enterprises and universities, in order to achieve a common cooperative innovation goal. It is a process of collaborative production of new knowledge between enterprises and universities.The collaborative interaction of knowledge sharing in industry-university cooperation is often based on a project. Through collaborative interaction, new knowledge can be generated and quickly transformed into enterprise technical capability and university scientific research and talent training advantages. The collaborative interaction process of knowledge sharing in industry-university cooperation is shown in Figure2. From this model framework, we can see that the collaborative interaction process of industry-university cooperation knowledge sharing can be divided into the following three stages.


## 4. Collaborative Interaction Model of Industry-University Cooperation Knowledge Sharing

Jones et al. [11] divided the subject into three types: thinking subject, which emphasizes the rational planning, reasoning, and thinking of the subject on its own goals, so as to reflect some intelligent characteristics. The second is reactive subject, which emphasizes the subject’s timely response to the environment and believes that intelligence comes from the interaction with the environment. The third is the compound subject, which emphasizes the comprehensive use of various methods to reflect the various characteristics of the subject.Industry-university cooperation knowledge sharing is a compound subject structure. In the process of realizing value creation, enterprises and universities are actually playing a role to complete organizational tasks and achieve organizational goals. Therefore, when analyzing the collaboration of industry-university cooperation knowledge sharing, in order to reflect the behavior reasoning process of the subject, we can adopt the integration idea to construct specific role-playing-based composite industry-university cooperation knowledge-sharing subject structure.


### 4.1. Basic Framework of Knowledge Sharing in Industry-University Cooperation Based on Role Play

In essence, industry-university cooperative knowledge sharing is a consortium composed of enterprises and universities through shared role-playing according to the goal of cooperative innovation. A shared role is actually an abstraction of two different organizations: enterprises and universities. Therefore, according to the research, from the relationship between the sharing role and the knowledge subject, we can define the subject entity of industry-university cooperation knowledge sharing as a combination of the planning ability of the corresponding sharing role, the behavior ability of the subject entity of industry-university cooperation knowledge sharing, and the structural framework supporting the operation of the subject of industry-university cooperation knowledge sharing. We have the following:Agent ≡ <R_ ABILITY, A_ ACT, AgentStr>Among them, the agent is represented as a knowledge-sharing entity of industry-university cooperation; R_ Ability is the planning ability of the corresponding role; A_ Act is the behavioral capacity of the knowledge sharing entity of industry-university cooperation; and AgentStr is the main structural framework.Knowledge-sharing capacity of industry-university cooperation is the instantiation of role capacity. These behavioral capabilities include the ability of technology application and market development of enterprises. The university’s scientific research ability, talent training ability, and knowledge transferability are exclusive and irreplaceable to some extent. Therefore, the process of role behavior capability instantiation is actually a process of determining whether the subject entity has the corresponding resources specified by the role before determining to play the specified role. The role planning ability is responsible for providing the basic knowledge, rules, and models of the subject’s thinking and decision-making activities. It is a reproducible and learnable soft resource. It is inherited by the subject playing the role in the process of role assignment. After determining to play the specified role, the subject will promise to carry out activities according to the goal and thinking mode of the role. In order to simplify the problem, the communication mechanism between agents is not considered separately but included in the state set and mapping in the definition.Here, the structural framework of the subject can be used to support the subject to combine its own behavior ability with the planning ability of the corresponding role, so as to ensure the realization of the role goal.The internal state base is mainly obtained by inheriting the knowledge base, model base, and rule base of the corresponding role. They can be adjusted and maintained according to the situation during the operation of the main body. The real-time state database is used to record other real-time data that may be used by the subject in behavior reasoning to reflect the internal state of the subject.The behavior inference engine is the thinking center of the subject. It is a decision-making organization to adjust the internal state of the subject and make behavior decision-making, negotiation, and coordination. Perception and action mainly reflect the interaction between the subject and the external environment. It is mainly guaranteed by the behavior ability of the subject individual.


### 4.2. Compound Collaborative Interaction Model of Industry-University Cooperation Knowledge Sharing Based on Role Play

The main structural framework based on role play gives the overall description of the main structure in the main organization. In order to further reflect the behavior characteristics of the main body, this paper proposes a composite industry-university cooperation knowledge-sharing collaborative interaction model based on role play, as shown in Figure3.Figure 3
Knowledge-sharing and interaction model of compound industry-university cooperation based on role play.As can be seen from Figure3, the role-playing-based compound industry-university cooperation knowledge-sharing collaborative interaction model conforms to the previous main structural framework. The whole model adopts a compound structure of three processes and four levels.Firstly, we analyze the process of industry-university cooperation and knowledge sharing. Previously, we divided the flow of knowledge-sharing elements of industry-university cooperation into three processes: self-owned knowledge selection and spillover, knowledge integration and common knowledge formation, and the absorption and application of common knowledge. (1) Own knowledge selection and spillover; it filters the organization’s own knowledge. First, it lists the collective knowledge expressed, summarized, and combined in the organization, and then identifies, classifies, and refines it. If it belongs to core knowledge, the knowledge cannot be shared and remains in the organization’s knowledge base or used it for sharing after core competence protection; otherwise, it should enter the shared knowledge base. (2) Knowledge integration and the formation of common knowledge: this process helps us establish a cooperative and shared knowledge base, which mainly includes three aspects: first is the screened knowledge from member organizations; the second is the external knowledge conducive to overall absorption and innovation; third is the newly created basic knowledge and applied knowledge in industry-university cooperation. The shared knowledge platform is based on the shared knowledge base, and all operations such as search and query for shared knowledge are carried out within the shared knowledge base. (3) Absorption and application of shared knowledge: this process is mainly to provide knowledge retrieval services for members of both parties, so as to facilitate the transfer of knowledge. At the same time, we can provide a personalized cooperation interface and dynamic interaction program for organizations by creating a knowledge-sharing network and portal service in its platform, so as to facilitate knowledge exchange, which is also the main way of knowledge sharing (mainly tacit knowledge) among cooperative organizations. The knowledge search engine service can provide various types of search types to help organizations and employees quickly locate knowledge; The service of the collaboration system can realize the synchronous and asynchronous interaction of various organizations based on the shared knowledge portal through forums, virtual communities, expert discussion groups, and so on. Knowledge-sharing evaluation service can enable organizations to more accurately locate their role in knowledge sharing of industry-university cooperation.Secondly, we make a simple analysis of some main modules. (1) Perception and action module: the perception and action module is related to the subject’s work field. Its main function is to ensure the perception and function of the environment through the behavior ability of the subject entity. At the same time, the perceived information will enter different processing levels according to urgency and complexity. (2) Interaction module: the main purpose of the interaction module is to ensure smooth information exchange between subjects, which is the basis of negotiation, cooperation, and coordination between subjects. In general, the interaction module involves the management of information such as low-level network protocol, communication protocol, interaction protocol, and high-level interaction strategy. (3) Behavioral reasoning module: the behavior reasoning module is the nerve center responsible for the subject’s behavior planning and decision-making. It is composed of three levels and is closely related to the interaction module. The first layer (the lowest layer) adopts the idea of reactive structure to make a real-time response to the environmental state directly according to the emergency behavior rules in an emergency or simple cases. The second layer receives environmental or interactive information and makes routine behavioral decision-making and management according to the information such as contracts, agreements, plans, or rules reached. The third layer is mainly responsible for the information that cannot be solved by the first two layers, such as the formulation and adjustment of various contracts, agreements, plans, rules, and strategies. It needs more intellectual support. Therefore, it is closely related to the decision support environment. The decision support environment can easily call the relevant models and knowledge in the basic data module and provide the corresponding man-machine interface when possible, so that decision-makers or domain experts can participate in the decision-making process. The implementation of the behavior reasoning module can adopt the main body basic structure diagram. (4) Knowledge module: the knowledge module is mainly used to ensure the relevant knowledge and data required by the interaction module. This information is initially obtained by inheriting the role planning capability and can be continuously revised during operation.Finally, we analyze the agent-based knowledge sharing and collaborative interaction strategy of industry-university cooperation. The three processes and four modules described above provide a basic framework to ensure interaction. With the support of this framework, conscious dialogue can be carried out between the subjects of industry-university cooperation and knowledge sharing. But in general, this is only a basic guarantee, and it does not involve the specific problem background. In practical application, the purpose of building a multiagent system, or agent interaction, is always to achieve a goal or solve some problems. Therefore, in order to promote the solution of problems through the interactive process, we must adopt corresponding interactive strategies for the specific problems faced by the knowledge-sharing subjects of industry-university cooperation. The choice of interaction strategy is related to the planning ability of the main role, such as the role’s individual knowledge base, organizational knowledge base, and related models, protocols, plans, rules, and so on. In the process of interaction, there may be role relationships such as resource dependence or conflicts of interest. The choice of interaction strategy is to solve these problems in the most appropriate way. Specifically, it is to select different interaction protocols for different interaction objects and different environmental conditions.For a relatively stable and closed problem environment, the interaction strategy of knowledge-sharing agents of industry-university cooperation can be analyzed, planned and designed in advance by designers in the design stage of the multiagent system. However, in the real environment, multiagent systems are mostly in a distributed, dynamic, and open environment. Therefore, it is very important and even necessary to endow the knowledge-sharing subjects of industry-university cooperation with the ability to formulate interactive strategies independently in the running state.According to the role-playing-based composite agent structure we analyzed earlier, the formulation and selection of agent interaction strategies for industry-university cooperation knowledge sharing belong to the processing content of the third layer of the behavior reasoning module. Therefore, the formulation and selection of interaction strategies are mainly obtained by the behavior reasoning module through reasoning and calculation according to the internal state data and combined with the real-time environment [12].As can be seen from Figure3, first, step a describes the behavior of the knowledge-sharing subject of industry-university cooperation in selecting interactive cooperation [13]. The condition for this behavior is that new problems are encountered, or the requirements for reselecting the protocol are determined through step C. This step requires three aspects of analysis: A1 is the analysis of current problems [14]; A2 is the expectations of the behavior of other subjects; A3 is the analysis of the alternative cooperation scheme, finally, giving the selected cooperation scheme, and entering step B. Step B describes the operation process of interactive behavior. First, the subject should make a commitment to the selected cooperation scheme to ensure that the interactive behavior is implemented in accordance with the requirements of the agreement; at the same time, the independent mechanism will monitor the implementation of the cooperation scheme by the subject during the interaction process [15]. If there is a situation beyond the provisions of the cooperation scheme, the exception handler will be triggered and step C will be entered. In step C, the exceptions will be analyzed and the current interactive cooperation scheme will be reevaluated. If the cooperation scheme has failed, go back to step a; otherwise, adjust the status and go to step B [16]. The types of exceptions include the completion of the cooperation scheme (as a special exception), the failure of the cooperation scheme, the change of the cooperation scheme by other subjects, etc.


## 4.1. Basic Framework of Knowledge Sharing in Industry-University Cooperation Based on Role Play

In essence, industry-university cooperative knowledge sharing is a consortium composed of enterprises and universities through shared role-playing according to the goal of cooperative innovation. A shared role is actually an abstraction of two different organizations: enterprises and universities. Therefore, according to the research, from the relationship between the sharing role and the knowledge subject, we can define the subject entity of industry-university cooperation knowledge sharing as a combination of the planning ability of the corresponding sharing role, the behavior ability of the subject entity of industry-university cooperation knowledge sharing, and the structural framework supporting the operation of the subject of industry-university cooperation knowledge sharing. We have the following:Agent ≡ <R_ ABILITY, A_ ACT, AgentStr>Among them, the agent is represented as a knowledge-sharing entity of industry-university cooperation; R_ Ability is the planning ability of the corresponding role; A_ Act is the behavioral capacity of the knowledge sharing entity of industry-university cooperation; and AgentStr is the main structural framework.Knowledge-sharing capacity of industry-university cooperation is the instantiation of role capacity. These behavioral capabilities include the ability of technology application and market development of enterprises. The university’s scientific research ability, talent training ability, and knowledge transferability are exclusive and irreplaceable to some extent. Therefore, the process of role behavior capability instantiation is actually a process of determining whether the subject entity has the corresponding resources specified by the role before determining to play the specified role. The role planning ability is responsible for providing the basic knowledge, rules, and models of the subject’s thinking and decision-making activities. It is a reproducible and learnable soft resource. It is inherited by the subject playing the role in the process of role assignment. After determining to play the specified role, the subject will promise to carry out activities according to the goal and thinking mode of the role. In order to simplify the problem, the communication mechanism between agents is not considered separately but included in the state set and mapping in the definition.Here, the structural framework of the subject can be used to support the subject to combine its own behavior ability with the planning ability of the corresponding role, so as to ensure the realization of the role goal.The internal state base is mainly obtained by inheriting the knowledge base, model base, and rule base of the corresponding role. They can be adjusted and maintained according to the situation during the operation of the main body. The real-time state database is used to record other real-time data that may be used by the subject in behavior reasoning to reflect the internal state of the subject.The behavior inference engine is the thinking center of the subject. It is a decision-making organization to adjust the internal state of the subject and make behavior decision-making, negotiation, and coordination. Perception and action mainly reflect the interaction between the subject and the external environment. It is mainly guaranteed by the behavior ability of the subject individual.


## 4.2. Compound Collaborative Interaction Model of Industry-University Cooperation Knowledge Sharing Based on Role Play

The main structural framework based on role play gives the overall description of the main structure in the main organization. In order to further reflect the behavior characteristics of the main body, this paper proposes a composite industry-university cooperation knowledge-sharing collaborative interaction model based on role play, as shown in Figure3.Figure 3
Knowledge-sharing and interaction model of compound industry-university cooperation based on role play.As can be seen from Figure3, the role-playing-based compound industry-university cooperation knowledge-sharing collaborative interaction model conforms to the previous main structural framework. The whole model adopts a compound structure of three processes and four levels.Firstly, we analyze the process of industry-university cooperation and knowledge sharing. Previously, we divided the flow of knowledge-sharing elements of industry-university cooperation into three processes: self-owned knowledge selection and spillover, knowledge integration and common knowledge formation, and the absorption and application of common knowledge. (1) Own knowledge selection and spillover; it filters the organization’s own knowledge. First, it lists the collective knowledge expressed, summarized, and combined in the organization, and then identifies, classifies, and refines it. If it belongs to core knowledge, the knowledge cannot be shared and remains in the organization’s knowledge base or used it for sharing after core competence protection; otherwise, it should enter the shared knowledge base. (2) Knowledge integration and the formation of common knowledge: this process helps us establish a cooperative and shared knowledge base, which mainly includes three aspects: first is the screened knowledge from member organizations; the second is the external knowledge conducive to overall absorption and innovation; third is the newly created basic knowledge and applied knowledge in industry-university cooperation. The shared knowledge platform is based on the shared knowledge base, and all operations such as search and query for shared knowledge are carried out within the shared knowledge base. (3) Absorption and application of shared knowledge: this process is mainly to provide knowledge retrieval services for members of both parties, so as to facilitate the transfer of knowledge. At the same time, we can provide a personalized cooperation interface and dynamic interaction program for organizations by creating a knowledge-sharing network and portal service in its platform, so as to facilitate knowledge exchange, which is also the main way of knowledge sharing (mainly tacit knowledge) among cooperative organizations. The knowledge search engine service can provide various types of search types to help organizations and employees quickly locate knowledge; The service of the collaboration system can realize the synchronous and asynchronous interaction of various organizations based on the shared knowledge portal through forums, virtual communities, expert discussion groups, and so on. Knowledge-sharing evaluation service can enable organizations to more accurately locate their role in knowledge sharing of industry-university cooperation.Secondly, we make a simple analysis of some main modules. (1) Perception and action module: the perception and action module is related to the subject’s work field. Its main function is to ensure the perception and function of the environment through the behavior ability of the subject entity. At the same time, the perceived information will enter different processing levels according to urgency and complexity. (2) Interaction module: the main purpose of the interaction module is to ensure smooth information exchange between subjects, which is the basis of negotiation, cooperation, and coordination between subjects. In general, the interaction module involves the management of information such as low-level network protocol, communication protocol, interaction protocol, and high-level interaction strategy. (3) Behavioral reasoning module: the behavior reasoning module is the nerve center responsible for the subject’s behavior planning and decision-making. It is composed of three levels and is closely related to the interaction module. The first layer (the lowest layer) adopts the idea of reactive structure to make a real-time response to the environmental state directly according to the emergency behavior rules in an emergency or simple cases. The second layer receives environmental or interactive information and makes routine behavioral decision-making and management according to the information such as contracts, agreements, plans, or rules reached. The third layer is mainly responsible for the information that cannot be solved by the first two layers, such as the formulation and adjustment of various contracts, agreements, plans, rules, and strategies. It needs more intellectual support. Therefore, it is closely related to the decision support environment. The decision support environment can easily call the relevant models and knowledge in the basic data module and provide the corresponding man-machine interface when possible, so that decision-makers or domain experts can participate in the decision-making process. The implementation of the behavior reasoning module can adopt the main body basic structure diagram. (4) Knowledge module: the knowledge module is mainly used to ensure the relevant knowledge and data required by the interaction module. This information is initially obtained by inheriting the role planning capability and can be continuously revised during operation.Finally, we analyze the agent-based knowledge sharing and collaborative interaction strategy of industry-university cooperation. The three processes and four modules described above provide a basic framework to ensure interaction. With the support of this framework, conscious dialogue can be carried out between the subjects of industry-university cooperation and knowledge sharing. But in general, this is only a basic guarantee, and it does not involve the specific problem background. In practical application, the purpose of building a multiagent system, or agent interaction, is always to achieve a goal or solve some problems. Therefore, in order to promote the solution of problems through the interactive process, we must adopt corresponding interactive strategies for the specific problems faced by the knowledge-sharing subjects of industry-university cooperation. The choice of interaction strategy is related to the planning ability of the main role, such as the role’s individual knowledge base, organizational knowledge base, and related models, protocols, plans, rules, and so on. In the process of interaction, there may be role relationships such as resource dependence or conflicts of interest. The choice of interaction strategy is to solve these problems in the most appropriate way. Specifically, it is to select different interaction protocols for different interaction objects and different environmental conditions.For a relatively stable and closed problem environment, the interaction strategy of knowledge-sharing agents of industry-university cooperation can be analyzed, planned and designed in advance by designers in the design stage of the multiagent system. However, in the real environment, multiagent systems are mostly in a distributed, dynamic, and open environment. Therefore, it is very important and even necessary to endow the knowledge-sharing subjects of industry-university cooperation with the ability to formulate interactive strategies independently in the running state.According to the role-playing-based composite agent structure we analyzed earlier, the formulation and selection of agent interaction strategies for industry-university cooperation knowledge sharing belong to the processing content of the third layer of the behavior reasoning module. Therefore, the formulation and selection of interaction strategies are mainly obtained by the behavior reasoning module through reasoning and calculation according to the internal state data and combined with the real-time environment [12].As can be seen from Figure3, first, step a describes the behavior of the knowledge-sharing subject of industry-university cooperation in selecting interactive cooperation [13]. The condition for this behavior is that new problems are encountered, or the requirements for reselecting the protocol are determined through step C. This step requires three aspects of analysis: A1 is the analysis of current problems [14]; A2 is the expectations of the behavior of other subjects; A3 is the analysis of the alternative cooperation scheme, finally, giving the selected cooperation scheme, and entering step B. Step B describes the operation process of interactive behavior. First, the subject should make a commitment to the selected cooperation scheme to ensure that the interactive behavior is implemented in accordance with the requirements of the agreement; at the same time, the independent mechanism will monitor the implementation of the cooperation scheme by the subject during the interaction process [15]. If there is a situation beyond the provisions of the cooperation scheme, the exception handler will be triggered and step C will be entered. In step C, the exceptions will be analyzed and the current interactive cooperation scheme will be reevaluated. If the cooperation scheme has failed, go back to step a; otherwise, adjust the status and go to step B [16]. The types of exceptions include the completion of the cooperation scheme (as a special exception), the failure of the cooperation scheme, the change of the cooperation scheme by other subjects, etc.


## 5. Conclusion

The knowledge sharing of industry-university cooperation is completed by different subjects. The external functional performance of any entity in the real environment is always determined by its internal structural characteristics. The internal structure of the subject is also closely related to its functional characteristics. Different environments, different application purposes, and different implementation methods make the subjects show differences in many aspects. Industry-university cooperative knowledge sharing is a cooperative relationship formed by two different types of subjects, enterprises, and universities, in order to achieve a common cooperative innovation goal. It is a process of collaborative production of new knowledge between enterprises and universities.



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*Source: 7343000-2022-02-15.xml*