Chan-Hung Yu

Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search

Programmatic reinforcement learning (PRL) has been explored for representing policies through programs as a means to achieve interpretability and generalization. Despite promising outcomes, current state-of-the-art PRL methods are hindered by sample inefficiency, necessitating tens of millions of pr…