AINeutralarXiv – CS AI · May 16/10
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EXPO: Stable Reinforcement Learning with Expressive Policies
Researchers introduce EXPO, a reinforcement learning algorithm that trains expressive policies (like diffusion models) more efficiently by avoiding direct value optimization. The method uses a lightweight Gaussian policy to edit actions from a base policy, achieving 2-3x improvements in sample efficiency for both offline-to-online and fine-tuning scenarios.