SuperSuit: Simple Microwrappers for Reinforcement Learning Environments

August 17, 2020 ยท Declared Dead ยท ๐Ÿ› arXiv.org

๐Ÿ’€ CAUSE OF DEATH: 404 Not Found
Code link is broken/dead
Authors J. K. Terry, Benjamin Black, Ananth Hari arXiv ID 2008.08932 Category cs.LG: Machine Learning Cross-listed cs.AI Citations 24 Venue arXiv.org Repository https://github.com/PettingZoo-Team/SuperSuit,and Last Checked 1 month ago
Abstract
In reinforcement learning, wrappers are universally used to transform the information that passes between a model and an environment. Despite their ubiquity, no library exists with reasonable implementations of all popular preprocessing methods. This leads to unnecessary bugs, code inefficiencies, and wasted developer time. Accordingly we introduce SuperSuit, a Python library that includes all popular wrappers, and wrappers that can easily apply lambda functions to the observations/actions/reward. It's compatible with the standard Gym environment specification, as well as the PettingZoo specification for multi-agent environments. The library is available at https://github.com/PettingZoo-Team/SuperSuit,and can be installed via pip.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

๐Ÿ“œ Similar Papers

In the same crypt โ€” Machine Learning

Died the same way โ€” ๐Ÿ’€ 404 Not Found