Disentangled World Models transfer semantic knowledge from distracting videos to RL world models via offline pretraining and latent distillation to improve sample efficiency under visual variations.
Generalizing consistency policy to visual rl with prior- itized proximal experience regularization
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Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning
Disentangled World Models transfer semantic knowledge from distracting videos to RL world models via offline pretraining and latent distillation to improve sample efficiency under visual variations.