Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems
Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems
David Klaška, Antonín Kučera, Martin Kurečka, Vít Musil, Petr Novotný, Vojtěch Řehák
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence
Main Track. Pages 171-179.
https://doi.org/10.24963/ijcai.2023/20
We consider the problem of synthesizing resilient and stochastically stable strategies for systems of cooperating agents striving to minimize the expected time between consecutive visits to selected locations in a known environment. A strategy profile is resilient if it retains its functionality even if some of the agents fail, and stochastically stable if the visiting time variance is small. We design a novel specification language for objectives involving resilience and stochastic stability, and we show how to efficiently compute strategy profiles (for both autonomous and coordinated agents) optimizing these objectives. Our experiments show that our strategy synthesis algorithm can construct highly non-trivial and efficient strategy profiles for environments with general topology.
Keywords:
Agent-based and Multi-agent Systems: MAS: Multi-agent planning
Agent-based and Multi-agent Systems: MAS: Coordination and cooperation
Planning and Scheduling: PS: Robot planning