Sampling-based Reactive Synthesis for Nondeterministic Hybrid Systems

• URL: http://arxiv.org/abs/2304.06876v3
• Date: Sat, 23 Dec 2023 22:13:05 GMT
• Title: Sampling-based Reactive Synthesis for Nondeterministic Hybrid Systems
• Authors: Qi Heng Ho, Zachary N. Sunberg, Morteza Lahijanian
• Abstract summary: This paper introduces a sampling-based strategy synthesis algorithm for nondeterministic hybrid systems. We model the evolution of the hybrid system as a two-player game, where the nondeterminism is an adversarial player. The aim is to synthesize a winning strategy -- a reactive (robust) strategy that guarantees the satisfaction of the goals under all possible moves of the adversarial player.
• Score: 20.0212772540119
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper introduces a sampling-based strategy synthesis algorithm for nondeterministic hybrid systems with complex continuous dynamics under temporal and reachability constraints. We model the evolution of the hybrid system as a two-player game, where the nondeterminism is an adversarial player whose objective is to prevent achieving temporal and reachability goals. The aim is to synthesize a winning strategy -- a reactive (robust) strategy that guarantees the satisfaction of the goals under all possible moves of the adversarial player. Our proposed approach involves growing a (search) game-tree in the hybrid space by combining sampling-based motion planning with a novel bandit-based technique to select and improve on partial strategies. We show that the algorithm is probabilistically complete, i.e., the algorithm will asymptotically almost surely find a winning strategy, if one exists. The case studies and benchmark results show that our algorithm is general and effective, and consistently outperforms state of the art algorithms.

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