Proceedings

First-Order Progression beyond Local-Effect and Normal Actions

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Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence. Main Track. Pages 3475-3483.

https://doi.org/10.24963/ijcai.2024/385

Abstract

One of the fundamental problems in reasoning about action is progression, which is to update a knowledge base according to the effects of an action into another knowledge base that retains all proper information. The problem is notoriously challenging, as in general, it requires second-order logic. Efforts have been made to find fragments where progression is first-order definable. Liu and Lakemeyer showed that for actions that have only local effects, progression is always first-order definable. They also generalized the result to so-called normal actions, that allow for non-local effects, as long as the affected fluent predicates only depend on local-effect ones, under certain restrictions on the knowledge base. In addition, they showed that for so-called proper+ knowledge bases, progression for normal actions can be efficient under reasonable assumptions. In this paper, we consider a larger class of theories, called the acyclic ones, that strictly subsumes normal actions. In such theories, dependencies between non-local effect fluent predicates are allowed, as long as they do not contain any cycles. We prove progression to be equally first-order definable for this class. Furthermore, under similar but stronger assumptions than those made by Liu and Lakemeyer, we show that progression is efficient as well.

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