aiqbench analysis
This research extends classical AGM belief revision postulates into a multi-agent framework using Kripke models for dynamic epistemic reasoning. It introduces generalized full-meet operators and event-based approaches to formally evaluate how agent beliefs evolve after acquiring new state properties. The work addresses theoretical challenges in defining consistent iterated revisions within complex distributed systems, advancing the formal foundations of AI planning.
A Study of Belief Revision Postulates in Multi-Agent Systems (Extended Version)
arXiv:2605.02249v2 Announce Type: replace 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.
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.
Artificial Intelligence (cs.AI)
arXiv:2605.02249 [cs.AI]
(or arXiv:2605.02249v2 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2605.02249 Focus to learn more arXiv-issued DOI via DataCite
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Full text under the publisher's open licence · 250 words