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SuperSuit: Simple Microwrappers for Reinforcement Learning Environments
August 17, 2020 ยท Declared Dead ยท ๐ arXiv.org
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.
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