Abstract
Belief change refers to the process in which an agent incorporates new information together with some pre-existing set of beliefs. We are interested in the situation where an agent must incorporate new information after the execution of actions with non-deterministic effects. In this case, the observation plays two distinct roles. First, it provides information about the current state of the world. Second, it provides information about the outcomes of any actions that have previously occurred. While the literature on belief change has extensively explored the former, we suggest that existing approaches to belief change have not explicitly considered how an agent uses observed information to determine the effects of non-deterministic actions. In this paper, we propose an approach in which action effects simply progress the agent’s underlying plausibility ordering over possible states. In the case of non-deterministic actions, new possible world trajectories are created and then subsequently dismissed as dictated by observations.
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Hunter, A. (2014). Belief Change and Non-deterministic Actions. In: Sokolova, M., van Beek, P. (eds) Advances in Artificial Intelligence. Canadian AI 2014. Lecture Notes in Computer Science(), vol 8436. Springer, Cham. https://doi.org/10.1007/978-3-319-06483-3_27
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DOI: https://doi.org/10.1007/978-3-319-06483-3_27
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06482-6
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