Sequence Modeling

Decision Transformer: Reinforcement Learning via Sequence Modeling

Decision Transformer recasts offline reinforcement learning as a conditional sequence modeling problem, using a causally masked Transformer to generate actions conditioned on desired return, past states, and actions. It matches or exceeds model-free offline RL baselines on Atari, OpenAI Gym, and Key-to-Door without any value function or policy gradient computation.