IJCAI 2023poster2 citations

Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems

David Klaška, Antonín Kučera, Martin Kurečka, Vít Musil, Petr Novotný, Vojtěch Řehák

Abstract

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.

Agent-based and Multi-agent Systems: MAS: Multi-agent planningAgent-based and Multi-agent Systems: MAS: Coordination and cooperationPlanning and Scheduling: PS: Robot planning
BibTeX
@inproceedings{ijcai2023p20,
  title     = {Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems},
  author    = {Klaška, David and Kučera, Antonín and Kurečka, Martin and Musil, Vít and Novotný, Petr and Řehák, Vojtěch},
  booktitle = {Proceedings of the Thirty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-23}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Edith Elkind},
  pages     = {171--179},
  year      = {2023},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2023/20},
  url       = {https://doi.org/10.24963/ijcai.2023/20},
}
Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems · IJCAI 2023