gym-hs: Haskell bindings for OpenAI Gymnasium
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A Haskell library that provides bindings to OpenAI Gymnasium environments. This library enables you to call any Gymnasium environment from Haskell code with a simple, type-safe API. It uses subprocess-based communication to interface with Python's Gymnasium library, providing full access to the rich ecosystem of reinforcement learning environments.
A full example using Gymnasium to implement a DQN solving CartPole is here: https://github.com/Xodarap/hs-gym-example
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- gym-hs-0.1.0.1.tar.gz [browse] (Cabal source package)
- Package description (as included in the package)
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Versions [RSS] | 0.1.0.0, 0.1.0.1 |
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Change log | CHANGELOG.md |
Dependencies | aeson (>=2.0 && <2.3), base (>=4.7 && <5), bytestring (>=0.10 && <0.13), containers (>=0.6 && <0.8), gym-hs, process (>=1.6 && <1.7), scientific (>=0.3 && <0.4), text (>=1.2 && <2.2), unordered-containers (>=0.2 && <0.3), vector (>=0.12 && <0.14) [details] |
Tested with | ghc ==9.6.7 |
License | MIT |
Copyright | 2025 Ben West |
Author | Ben West |
Maintainer | xodarap00@gmail.com |
Category | AI, Machine Learning, Reinforcement Learning |
Home page | https://github.com/Xodarap/haskell-gymnasium |
Bug tracker | https://github.com/Xodarap/haskell-gymnasium/issues |
Source repo | head: git clone https://github.com/Xodarap/haskell-gymnasium |
Uploaded | by benthamite at 2025-07-25T20:26:15Z |
Distributions | |
Executables | gym-hs-example |
Downloads | 5 total (5 in the last 30 days) |
Rating | (no votes yet) [estimated by Bayesian average] |
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Status | Docs available [build log] Last success reported on 2025-07-25 [all 1 reports] |