Skip to content

Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.

License

Notifications You must be signed in to change notification settings

TTF2050/decision-transformer

 
 

Repository files navigation

Decision Transformer

Lili Chen*, Kevin Lu*, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas†, and Igor Mordatch†

*equal contribution, †equal advising

A link to our paper can be found on arXiv.

Overview

Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling. Contains scripts to reproduce experiments.

image info

Instructions

We provide code in two sub-directories: atari containing code for Atari experiments and gym containing code for OpenAI Gym experiments. See corresponding READMEs in each folder for instructions; scripts should be run from the respective directories. It may be necessary to add the respective directories to your PYTHONPATH.

Citation

Please cite our paper as:

@article{chen2021decisiontransformer,
  title={Decision Transformer: Reinforcement Learning via Sequence Modeling},
  author={Lili Chen and Kevin Lu and Aravind Rajeswaran and Kimin Lee and Aditya Grover and Michael Laskin and Pieter Abbeel and Aravind Srinivas and Igor Mordatch},
  journal={arXiv preprint arXiv:2106.01345},
  year={2021}
}

Note: this is not an official Google or Facebook product.

License

MIT

About

Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 96.6%
  • Dockerfile 1.8%
  • Shell 1.6%