Diffusion-Reinforcement Learning Hierarchical Motion Planning in Adversarial Multi-agent Games

Reinforcement Learning- (RL-)based motion planning has recently shown the potential to outperform traditional approaches from autonomous navigation to robot manipulation. In this work, we focus on a motion planning task for an evasive target in a partially observable multi-agent adversarial pursuit-...

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Hauptverfasser:	Wu, Zixuan, Ye, Sean, Natarajan, Manisha, Gombolay, Matthew C
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Computer Science - Multiagent Systems Computer Science - Robotics
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