A Study of Belief Revision Postulates in Multi-Agent Systems (Extended Version)

arXiv cs.AI / 5/5/2026

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Key Points

  • The paper studies how beliefs in epistemic planning update in multi-agent systems after one agent learns a new property about states.
  • Using the standard single multi-agent Kripke model representation of agents’ beliefs, it generalizes the classical AGM belief revision postulates to a multi-agent setting.
  • It presents concrete multi-agent belief revision operators, including a generalized full-meet approach that satisfies all generalized AGM postulates.
  • The authors also extend belief-revision postulates to iterated revision and introduce an event-model-based operator, while discussing challenges in defining Kripke-model epistemic operators that satisfy all iterated postulates.

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.