People#

We would like to thank members of the Stanford PAIR Group for their support and feedback on this project. These people in particular have made the following contributions at different stages of this project:

• Rohun Kulkarni (assistance with collecting real robot datasets and running real robot experiments)

• Albert Tung (assistance with collecting simulation datasets using the RoboTurk system)

• Fei Xia (egl_probe library, which helped us run experiments on lab clusters)

• Jim Fan (providing support for running experiments on lab clusters)

Codebases#

• Our Config class (see config/config.py) was adapted from addict.

• The BCQ, CQL, and TD3-BC author-provided implementations were used as a reference for our implementations.

• The TanhWrappedDistribution class in models/distributions.py was adapted from rlkit.

• Support for training distributional critics (see BCQ_Distributional in algos/bcq.py) was adapted from Acme. It also served as a useful reference for implementing Gaussian Mixture Model (GMM) policies.

• Our transformer implementation was adapted from the excellent minGPT codebase.

We wholeheartedly welcome the community to contribute to our project through issues and pull requests. New contributors will be added to the list above.