为多智能体系统提出可形式化评估信念更新的理论框架
A Study of Belief Revision Postulates in Multi-Agent Systems (Extended Version)
- 将经典AGM信念修正公理扩展至多智能体场景
- 构造满足所有新公理的广义全交信念更新算子
- 揭示迭代信念更新在克里普克模型上的实现难题
我们研究了认知规划中的信念修正问题，即某个智能体获得某一状态属性信念后，所有智能体的信念将如何变化。基于多智能体克里普克模型对智能体信念的标准表示，我们将经典的AGM信念修正公理推广到多智能体环境，旨在为动态认知推理框架提供形式化评估标准。作为满足所有推广后公理的简单算子示例，我们提出了广义全交多智能体信念修正。此外，我们还定义了标准公理在迭代修正下的推广形式，提出一种基于事件模型的更复杂修正算子，并讨论了在克里普克模型上定义能同时满足所有推广后公理的多智能体信念算子所面临的潜在问题。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。