Summary of Gymnasium: a Standard Interface For Reinforcement Learning Environments, by Mark Towers et al.
Gymnasium: A Standard Interface for Reinforcement Learning Environments
by Mark Towers, Ariel Kwiatkowski, Jordan Terry, John U. Balis, Gianluca De Cola, Tristan Deleu, Manuel Goulão, Andreas Kallinteris, Markus Krimmel, Arjun KG, Rodrigo Perez-Vicente, Andrea Pierré, Sander Schulhoff, Jun Jet Tai, Hannah Tan, Omar G. Younis
First submitted to arxiv on: 24 Jul 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Digital Libraries (cs.DL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Reinforcement Learning (RL) is a rapidly growing field with the potential to revolutionize artificial intelligence. However, RL research is hindered by the lack of standardization in environment and algorithm implementations, making it challenging for researchers to compare and build upon each other’s work. Gymnasium, an open-source library, aims to tackle this issue by providing a standard API for RL environments. Its main feature is a set of abstractions allowing wide interoperability between environments and training algorithms, enabling easier development and testing of RL algorithms. Gymnasium also offers easy-to-use environments, tools for customizing environments, and tools ensuring reproducibility and robustness of RL research. This unified framework significantly streamlines the process of developing and testing RL algorithms, allowing researchers to focus on innovation rather than implementation details. By providing a standardized platform for RL research, Gymnasium drives forward the field and unlocks its full potential. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Reinforcement Learning is a way for computers to learn from experience. Right now, it’s hard for scientists to compare their work or build upon each other’s ideas because different computer programs use different ways of doing things. A new tool called Gymnasium helps solve this problem by providing a standard way for different programs to talk to each other and share information. This makes it easier for scientists to develop and test new ideas in Reinforcement Learning, which could lead to big advancements in artificial intelligence. |
Keywords
* Artificial intelligence * Reinforcement learning
