Appending autoencoder-derived trajectory encodings to the state space improves offline RL transfer to new CartPole dynamics compared with BCQ, though the effect is small in some environments.
Off-policy deep reinforcement learning without exploration
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TEA: Trajectory Encoding Augmentation for Robust and Transferable Policies in Offline Reinforcement Learning
Appending autoencoder-derived trajectory encodings to the state space improves offline RL transfer to new CartPole dynamics compared with BCQ, though the effect is small in some environments.