We present a method for reasoning about fault-tolerance in unbounded robotic swarms. We introduce a novel semantics that accounts for the probabilistic nature of both the swarm and possible malfunctions, as well as the unbounded nature of swarm systems. We define and interpret a variant of probabilistic linear-time temporal logic on the resulting executions, including those arising from faulty behaviour by some of the agents in the swarm. We specify the decision problem of parameterised fault-tolerance, which concerns determining whether a probabilistic specification holds under possibly faulty behaviour. We outline a verification procedure that we implement and use to study a foraging protocol from swarm robotics, and report the experimental results obtained.
CITATION STYLE
Lomuscio, A., & Pirovano, E. (2020). Verifying fault-tolerance in probabilistic swarm systems. In IJCAI International Joint Conference on Artificial Intelligence (Vol. 2021-January, pp. 325–331). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2020/46
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