Q-Chunking
First page
Paper summary
Q-chunking is a reinforcement learning approach that uses action chunking to improve offline-to-online learning in long-horizon, sparse-reward tasks. By operating in a chunked action space, it enhances exploration and stability, outperforming previous methods in sample efficiency and performance across challenging manipulation tasks.