Learning-based metareasoning for decision-making in multi-agent pursuit-evasion games
Prannoy Namala,
Jeffrey W. Herrmann
Abstract:Reinforcement Learning (RL) has become a widely used approach for pursuit-evasion games. However, the behavior of such RL models is hard to analyze, often leading to a lack of trust. This paper describes a study in which we used machine learning (ML) approaches to develop metareasoning policies that control pursuers’ strategies. The proposed approach enables pursuer agents to capture a faster evader by choosing simple pursuit strategies collaboratively. The results show that some metareasoning policies perform… Show more
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