Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems
| Authors | |
|---|---|
| Year of publication | 2023 |
| Type | Article in Proceedings |
| Conference | Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI 2023, |
| MU Faculty or unit | |
| Citation | |
| web | Paper URL |
| Doi | http://dx.doi.org/10.24963/ijcai.2023/20 |
| Keywords | Multi-agent systems; strategy synthesis |
| Attached files | |
| Description | 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. |
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