Automated Verification of Propositional Agent Abstraction for Classical Planning via CTLK Model Checking
DOI:
https://doi.org/10.1609/aaai.v37i5.25796Keywords:
KRR: Action, Change, and Causality, PRS: Other Foundations of Planning, Routing & SchedulingAbstract
Abstraction has long been an effective mechanism to help find a solution in classical planning. Agent abstraction, based on the situation calculus, is a promising explainable framework for agent planning, yet its automation is still far from being tackled. In this paper, we focus on a propositional version of agent abstraction designed for finite-state systems. We investigate the automated verification of the existence of propositional agent abstraction, given a finite-state system and a mapping indicating an abstraction for it. By formalizing sound, complete and deterministic properties of abstractions in a general framework, we show that the verification task can be reduced to the task of model checking against CTLK specifications. We implemented a prototype system, and validated the viability of our approach through experimentation on several domains from classical planning.Downloads
Published
2023-06-26
How to Cite
Luo, K. (2023). Automated Verification of Propositional Agent Abstraction for Classical Planning via CTLK Model Checking. Proceedings of the AAAI Conference on Artificial Intelligence, 37(5), 6475-6482. https://doi.org/10.1609/aaai.v37i5.25796
Issue
Section
AAAI Technical Track on Knowledge Representation and Reasoning