A COOPERATION METHOD VIA METAPHOR OF EXPLANATION

This paper proposes a new method to improve cooperation in concurrent systems within the framework of Multi-Agent Systems (MAS). Since subsy stems work concurrently, achieving appropriate cooperation among them is important to improve the effectiveness of the overall system. When subsystems are modeled as agents, it is easy to explicitly deal with t he interactions among them since they can be modeled naturally as comm unication among agents with intended information. Contrary to previous approaches which provided the syntax of communication protocols witho ut semantics, we focus on the semantics of cooperation in MAS and aim at allowing agents to exploit the communicated information for coopera tion. This is attempted by utilizing more coarse-grained communication based on the different perspective for the balance between Formality and richness of communication contents so that each piece of communica tion contents can convey more meaningful information in application do mains. In our approach agents cooperate each other by giving Feedbacks based on the metaphor of explanation which is widely used in human in teractions, in contrast to previous approaches which use direct orders given by the leader based on the pre-defined cooperation strategies. Agents show the difference between the proposal and counterproposals f or it, which are constructed with respect to the Former and given as t he feedbacks in the easily understandable terms For the receiver. From the comparison of proposals agents retrieve the information on which parts are agreed and disagreed by the relevant agents, and reflect the analysis in their following behavior. Furthermore, communication cont ents are annotated by agents to indicate the degree of importance in d ecision making for them, which contributes to making explanations or f eedbacks more understandable. Our cooperation method was examined thro ugh experiments on the design of micro satellites and the result showe d that it was effective to some extent to facilitate cooperation among agents.