AgenticRL: Agentic Reinforcement Learning with Self-Refinement for Complex UAV Navigation
AgenticRL is a multimodal closed-loop framework for autonomous robots that uses role-specialized agents to generate executable rewards, diagnose failures, and refine policies. It achieves high success rates in UAV navigation tasks and is a significant advancement in AI agent development.
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