From Weak Data to Strong Policy: Q-Targets Enable Provable In-Context Reinforcement Learning
Q-Target Pretrained Transformers is proposed, which keeps the context-conditioned Transformer architecture but replaces behavior cloning with a Bellman-style Q-target objective, and learns to use rewards and transitions in the context to estimate action values, rather than simply imitating the behavior policy.
Yi-Chen Lin, Xu-Yuan Xiong, Xue Wang et al.
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