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.
Authors
- Jens Claßen (ORCID: https://orcid.org/0000-0002-0395-1907)
- Daxin Liu (ORCID: https://orcid.org/0000-0002-0378-3683)
Institutions
- Roskilde University (DK)
- Nanjing University (CN)
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
- Field-Weighted Citation Impact
- 0.00