Goal-constrained Planning Domain Model Verification of Safety Properties
This work improves the reliability of planning-based automated systems by reducing false alarms in safety verification, though it is incremental in nature.
The paper addresses the problem of false positives in planning domain model verification by introducing the concept of valid planning counterexamples and demonstrating how to use model checkers and state trajectory constraints to avoid returning invalid ones.
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.