CoUR uses LLMs for efficient RL reward design through uncertainty quantification and similarity selection, achieving better performance and lower evaluation costs on IsaacGym and Bidexterous Manipulation benchmarks.
Tree of uncertain thoughts reasoning for large language models
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Chain of Uncertain Rewards with Large Language Models for Reinforcement Learning
CoUR uses LLMs for efficient RL reward design through uncertainty quantification and similarity selection, achieving better performance and lower evaluation costs on IsaacGym and Bidexterous Manipulation benchmarks.