The repository provides the official implementation of Decision Transformer, a 2021 paper that treats reinforcement learning as a sequence modeling problem. It uses a transformer architecture to predict actions based on past states, returns, and actions, enabling offline RL without explicit value estimation. The codebase includes scripts for Atari games and OpenAI Gym environments to reproduce the paper’s experimental results.