訓練你的第一個 Decision Transformer：Hugging Face 官方強化學習教學
Original: Train your first Decision Transformer
Decision Transformer (DT) is an innovative architecture that reframes reinforcement learning (RL) as a sequence modeling problem…
本教學為 Hugging Face 官方指南，介紹如何訓練第一個 Decision Transformer (DT)。DT 將強化學習（RL）重新框架為序列建模問題，利用 Transformer 架構預測動作。教學涵蓋離線強化學習（Offline RL）的概念、如何使用 Hugging Face 的 `transformers` 庫與 `DecisionTransformerModel`，並在 Gym 環境中進行實作與評估，是結合 NLP 技術與控制任務的經典入門。
Decision Transformer (DT) is an innovative architecture that reframes reinforcement learning (RL) as a sequence modeling problem. Traditional reinforcement learning typically relies on value function estimation (such as Q-learning) or policy gradient methods, whereas DT directly applies a GPT-style Transformer architecture, treating states, actions, and returns-to-go (RTG) as sequential data and training by predicting the next action.
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