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Jinbin Qiao

2 accepted papers

2025

LaRes: Evolutionary Reinforcement Learning with LLM-based Adaptive Reward Search

NeurIPS 2025poster

The integration of evolutionary algorithms (EAs) with reinforcement learning (RL) has shown superior performance compared to standalone methods. However, previous research focuses on exploration in policy parameter space, while overlooking the reward function search. To bridge this gap, we propose *…

Cited by 0SourcecodeScholar
2025

R*: Efficient Reward Design via Reward Structure Evolution and Parameter Alignment Optimization with Large Language Models

ICML 2025poster

Reward functions are crucial for policy learning. Large Language Models (LLMs), with strong coding capabilities and valuable domain knowledge, provide an automated solution for high-quality reward design. However, code-based reward functions require precise guiding logic and parameter configuratio…

Cited by 0SourcePDFScholar