Non-Deterministic Planning for Hyperproperty Verification
<|reference_start|>Non-Deterministic Planning for Hyperproperty Verification: Non-deterministic planning aims to find a policy that achieves a given objective in an environment where actions have uncertain effects, and the agent - potentially - only observes parts of the current state. Hyperproperties are properties that relate multiple paths of a system and can, e.g., capture security and information-flow policies. Popular logics for expressing temporal hyperproperties - such as HyperLTL - extend LTL by offering selective quantification over executions of a system. In this paper, we show that planning offers a powerful intermediate language for the automated verification of hyperproperties. Concretely, we present an algorithm that, given a HyperLTL verification problem, constructs a non-deterministic multi-agent planning instance (in the form of a QDec-POMDP) that, when admitting a plan, implies the satisfaction of the verification problem. We show that for large fragments of HyperLTL, the resulting planning instance corresponds to a classical, FOND, or POND planning problem. We implement our encoding in a prototype verification tool and report on encouraging experimental results.<|reference_end|>
@article{beutner2024non-deterministic,
    title={Non-Deterministic Planning for Hyperproperty Verification},
    author={Raven Beutner, Bernd Finkbeiner},
    journal={arXiv preprint arXiv:2405.13488},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.13488},
    primaryClass={cs.LO cs.AI cs.FL}
}