Heuristic reasoning about uncertainty: an artificial intelligence approach
Heuristic reasoning about uncertainty: an artificial intelligence approach
Artificial Intelligence
ARCHON: an architecture for multi-agent systems
ARCHON: an architecture for multi-agent systems
Abstract argumentation systems
Artificial Intelligence
Environmental decision support: a multi-agent approach
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Belief Revision Through the Belief-Function Formalism in a Multi-Agent Environment
ECAI '96 Proceedings of the Workshop on Intelligent Agents III, Agent Theories, Architectures, and Languages
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The ability to solve conflicting beliefs is crucial for multiagent systems where the information is dynamic, incomplete and distributed over a group of autonomous agents. The proposed distributed belief revision approach consists of a distributed truth maintenance system and a set of autonomous belief revision methodologies. The agents have partial views and, frequently, hold disparate beliefs which are automatically detected by system's reason maintenance mechanism. The nature of these conflicts is dynamic and requires adequate methodologies for conflict resolution. The two types of conflicting beliefs addressed in this paper are Context Dependent and Context Independent Conflicts which result, in the first case, from the assignment, by different agents, of opposite belief statuses to the same belief, and, in the latter case, from holding contradictory distinct beliefs. The belief revision methodology for solving Context Independent Conflicts is, basically, a selection process based on the assessment of the credibility of the opposing belief statuses. The belief revision methodology for solving Context Dependent Conflicts is, essentially, a search process for a consensual alternative based on a "next best" relaxation strategy.