On Action Theories with Iterable First-Order Progression

We study the first-order definability of progression for situation calculus action theories with a focus on the iterability of progression. Progression, the task of updating a knowledge base according to actions' effects so that proper information is retained, is notoriously challenging as it in general requires second-order logic. Exceptions where progression is first-order like local-effect actions and normal actions impose certain syntax constraints on action theories to eliminate second-order quantifiers in the progressed knowledge base. Unfortunately, the progressed result might not satisfy the constraints again, making it impossible to apply first-order progression iteratively. In this paper, we first lift the existing result on first-order progression for normal actions by allowing disjunctions in the knowledge base. As a result, we obtain an action theory whose type is called disjunctive normal, which is iteratively first-order progressable. Second, we propose a new class of action theories, called PANACK, that strictly subsumes the disjunctive normal ones, and we show that it remains iteratively first-order progressable as well.

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Publication Details

Journal
Proceedings of the AAAI Conference on Artificial Intelligence
Published
2025-04-11
DOI
https://doi.org/10.1609/aaai.v39i14.33649
Primary Topic
Computability, Logic, AI Algorithms
Type
article
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article

On Action Theories with Iterable First-Order Progression

Jens Claßen, Daxin Liu
Proceedings of the AAAI Conference on Artificial Intelligence
Computability, Logic, AI Algorithms
article

On Action Theories with Iterable First-Order Progression

Jens Claßen, Daxin Liu
article en

Abstract

We study the first-order definability of progression for situation calculus action theories with a focus on the iterability of progression. Progression, the task of updating a knowledge base according to actions' effects so that proper information is retained, is notoriously challenging as it in general requires second-order logic. Exceptions where progression is first-order like local-effect actions and normal actions impose certain syntax constraints on action theories to eliminate second-order quantifiers in the progressed knowledge base. Unfortunately, the progressed result might not satisfy the constraints again, making it impossible to apply first-order progression iteratively. In this paper, we first lift the existing result on first-order progression for normal actions by allowing disjunctions in the knowledge base. As a result, we obtain an action theory whose type is called disjunctive normal, which is iteratively first-order progressable. Second, we propose a new class of action theories, called PANACK, that strictly subsumes the disjunctive normal ones, and we show that it remains iteratively first-order progressable as well.

Proceedings of the AAAI Conference on Artificial IntelligenceVol. 39(14)
Roskilde University (DK), Nanjing University (CN)
Openalex Percentile: Top 89%
Computability, Logic, AI Algorithms
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On Action Theories with Iterable First-Order Progression — Jens Claßen, Daxin Liu · Proceedings of the AAAI Conference on Artificial Intelligence (2025) | TGRS Research Map | TGRS