2018/11/22 by Anas Shrinah, Kerstin Eder, Shrinah, Anas +1
Computer Science · #AI-based Problem Solving and Planning #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Formal Methods in Verification #Model-Driven Software Engineering Techniques
paper · pdf · doi:10.48550/arxiv.1811.09231
openalex publication_date 2018/11/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The verification of planning domain models is crucial to ensure the safety, integrity and correctness of planning-based automated systems. This task is usually performed using model checking techniques. However, unconstrained application of model checkers to verify planning domain models can result in false positives, i.e.counterexamples that are unreachable by a sound planner when using the domain under verification during a planning task. In this paper, we discuss the downside of unconstrained planning domain model verification. We then introduce the notion of a valid planning counterexample, and demonstrate how model checkers, as well as state trajectory constraints planning techniques, should be used to verify planning domain models so that invalid planning counterexamples are not returned.