Belief Change with Uncertain Action Histories

Author:

Hunter Aaron,Delgrande James

Abstract

We consider the iterated belief change that occurs following an alternating sequence of actions and observations. At each instant, an agent has beliefs about the actions that have occurred as well as beliefs about the resulting state of the world. We represent such problems by a sequence of ranking functions, so an agent assigns a quantitative plausibility value to every action and every state at each point in time. The resulting formalism is able to represent fallible belief, erroneous perception, exogenous actions, and failed actions. We illustrate that our framework is a generalization of several existing approaches to belief change, and it appropriately captures the non-elementary interaction between belief update and belief revision.

Publisher

AI Access Foundation

Subject

Artificial Intelligence

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Mixed Iterated Revisions: Rationale, Algorithms, and Complexity;ACM Transactions on Computational Logic;2023-05-10

2. A Logic Programming Approach to Regression Based Repair of Incorrect Initial Belief States;Practical Aspects of Declarative Languages;2021

3. Reasoning About Action and Change;A Guided Tour of Artificial Intelligence Research;2020

4. Revision and Updates in Possibly Action-Occurrence-Incomplete Narratives;PRIMA 2017: Principles and Practice of Multi-Agent Systems;2017

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