A self-diagnosable multi-agent system considering dynamic communication load sharing

This paper proposes a self-diagnosable multi-agent system. A self-diagnosable algorithm has been proposed for multi-agent systems. This conventional algorithm makes every agent diagnose all other agents, but it has a problem that the more agents are included in a system, the more communications traffic increases. To solve the problem, this paper proposes a framework of multi-agent system that divides and deals with in parallel domains for mutual diagnosis to mitigate the communications between agents. Our approach introduces middle agents that do not interaction with basic client agents and we have developed a dynamic highly structured system that dynamically reconstitutes system configuration. The proposed method has been applied to a multi-agent system that forms a circle autonomously. Numerical experiments show that the proposed method needs much less communications than the conventional one.