🤖 AI Summary
This study addresses the challenge of coordinating collective belief updates in multi-agent systems when individual agents acquire new beliefs. It presents the first systematic extension of the classical AGM belief revision axioms—and their iterated variants—to multi-agent settings. Building upon multi-agent Kripke models and dynamic epistemic logic, the work develops a formal framework for belief revision that integrates event models and introduces a generalized full-intersection belief revision operator. This operator satisfies all generalized AGM postulates, effectively supporting dynamic and interactive belief updates among multiple agents, while also providing a rigorous theoretical foundation and a concrete implementation pathway for iterated multi-agent belief revision.
📝 Abstract
We investigate the belief revision problem in epistemic planning, i.e., what will be the beliefs of all agents in a multi-agent system after an agent gains the belief in some state property. Based on the standard representation in epistemic planning of agents' beliefs via a single multi-agent Kripke model, we generalize the classical AGM belief revision postulates to the multi-agent setting, with the aim to provide a formal framework for evaluating dynamic epistemic reasoning frameworks in which the beliefs of all agents as the result of actions are computed. As an example of a simple operator that satisfies all of the generalized AGM postulates, we present generalized full-meet multi-agent belief revision. We moreover define a generalization of the standard postulates for iterated revision, present a more sophisticated, event model based revision operator, and discuss the potential issues in defining an epistemic operator on Kripke models that can satisfy all of the generalized postulates for iterated multi-agent belief revision.