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This seminar introduces Decision Transformer, which frames reinforcement learning as conditional sequence modeling. It describes how a causally masked Transformer uses desired returns, past states, and actions to generate future actions, and reports results on Atari, OpenAI Gym, and Key-to-Door tasks.
