An Adaptive and Reliable System Based on Interdependence between Agents
A multiagent system (MAS) has recently gained public attention as a technique to solve competition and cooperation in distributed systems. However, MAS's vulnerability due to the propagation of failures prevents from applying to a large scale system. Then, this paper proposes a general composition technique to improve its reliability easily applied to the existent MAS. Proposed system monitors messages between agents to detect undesirable behaviors (failures). Collecting related information, the system generates global information of interdependence between agents and expresses it in a graph. This interdependence graph enables us to detect or predict undesirable behaviors. This paper also shows that the system can optimize performance of MAS and improve adaptively its reliability under complicated and dynamic environment by applying the global information acquired from analysis of the interdependence graph to a replication system.