An abstraction-refinement framework for verifying strategic properties in multi-agent systems with imperfect information - Université d'Évry Access content directly
Journal Articles Artificial Intelligence Year : 2023

An abstraction-refinement framework for verifying strategic properties in multi-agent systems with imperfect information

Abstract

We investigate the verification of Multi-Agent Systems against strategic properties expressed in Alternating-time Temporal Logic under the assumptions of imperfect information and perfect recall. To this end, we develop a three-valued semantics for concurrent game structures upon which we define an abstraction method. We prove that concurrent game structures with imperfect information admit perfect information abstractions that preserve three-valued satisfaction. Furthermore, to deal with cases in which the value of a specification is undefined, we develop a novel automata-theoretic technique for the linear-time logic (LTL), then apply it to finding “failure” states. The latter can then be fed into a refinement procedure, thus providing a sound, albeit incomplete, verification method. We illustrate the overall procedure in a variant of the Train Gate Controller scenario and a simple voting protocol under imperfect information and perfect recall. We also present an implementation of our procedure and provide preliminary experimental results.
No file

Dates and versions

hal-03960910 , version 1 (28-01-2023)

Identifiers

Cite

Francesco Belardinelli, Angelo Ferrando, Vadim Malvone. An abstraction-refinement framework for verifying strategic properties in multi-agent systems with imperfect information. Artificial Intelligence, 2023, 316, pp.103847. ⟨10.1016/j.artint.2022.103847⟩. ⟨hal-03960910⟩
75 View
0 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More