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The paper proposes the model for negotiating intelligent agents’ ontologies in cohesive hybrid intelligent multi-agent systems. Intelligent agent in this study will be called relatively autonomous software entity with developed domain models and goal-setting mechanisms. When such agents have to work together within single hybrid intelligent multi-agent systems to solve some problem, the working process “go wild”, if there are significant differences between the agents’ “points of view” on the domain, goals and rules of joint work. In this regard, in order to reduce labor costs for integrating intelligent agents into a single system, the concept of cohesive hybrid intelligent multi-agent systems was proposed that implement mechanisms for negotiating goals, domain models and building a protocol for solving the problems posed. The presence of these mechanisms is especially important when building intelligent systems from intelligent agents created by various independent development teams.

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The work is devoted to the issues of building cohesive hybrid intelligent multi-agent systems that implement the following mechanisms for ensuring the joint work of heterogeneous agents: coordination of goals and agent ontologies, development of the problem solving protocol. These mechanisms are similar to the processes that occur in long-standing expert teams. In them, experts, interacting in the course of solving problems, exchange views, knowledge, take into account each other’s goals, establish formal and informal norms of communication. In the paper, in particular, a method for estimating the similarity of ontologies is considered, which is the part of the method for estimating the cohesion of agents of the hybrid intelligent multi-agent system. The estimation of cohesion is used by system’s agents as the interaction effectiveness criterion when making decisions about the need to converge goals, ontologies or correction of the interaction protocol.

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