Episodic Memory-Guided Controllable Experience Synthesis for Reinforcement Learning
EMES is the first work to incorporate EM into controllable DMs and to leverage EM for guiding data synthesis in RL, and introduces a hashing-based state representation for EM to improve its efficiency and further boost the quality of synthetic data.
Xiao Ma, Tian Li, Wu-Jun Li
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