A DISTRIBUTED APPROACH FOR MULTIPLE MODEL DIAGNOSIS OF PHYSICAL SYSTEMS

In the 1990s Agent-Based Systems (ABS) have acquired the same importan ce as Knowledge-Based Systems (KBS) during the 1980s. Agent technology appeal is due to the benefits that agent-based organization and coord ination allow in designing cooperative problem-solving systems. In rec ent works on distributed artificial intelligence (DAI), researchers ha ve tried to define more precisely the role of an intelligent agent, i. e., of the computational entity that shares the accomplishment of a sp ecific global goal via collaborative schemes. Although important progr ess has been made in this field, the systematic design of DAT-oriented systems still remains a hard task. In this paper, we attempt to defin e a general diagnostic engine designed to allow cooperative problem so lving within a web of knowledge-based agents. A framework of a coopera tive diagnostic engine is proposed, where the diagnosis of physical sy stems is accomplished in a parallel and distributed universe of intell igent actors. To reach this goal, we formalize an organizational diagn ostic knowledge structure which defines different deep models and task s in order to better distinguish between structure and behavior. Such organization induces different cooperation schemes within the agents i n order to improve the diagnostic ability in the distributed processin g. (C) Elsevier Science Inc. 1997.