Reinforcement Learning Behavioral Control for Nonlinear Autonomous System

Behavior-based autonomous systems rely on human intelligence to resolve multi-mission conflicts by designing mission priority rules and nonlinear controllers. In this work, a novel two-layer reinforcement learning behavioral control (RLBC) method is proposed to reduce such dependence by trial-and-er...

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Veröffentlicht in:IEEE/CAA journal of automatica sinica 2022-09, Vol.9 (9), p.1561-1573
Hauptverfasser: Zhang, Zhenyi, Mo, Zhibin, Chen, Yutao, Huang, Jie
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Sprache:eng
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