This package contains OpenAI Gym environment designed for training RL agents to bring CartPole upright and its further balancing. The environment is automatically registered under id: single-cartpole-custom-v0, so it can be easily used by RL agent training libraries, such as StableBaselines3.
At the https://github.com/marek-robak/Single-cartpole-custom-gym-env-for-reinforcement-learning.git you can find a detailed description of the environment, along with a description of the package installation and sample code made to train and evaluate agents in this environment.
This environment was created for the needs of my bachelor's thesis, available at https://www.ap.uj.edu.pl/diplomas/151837/ site.
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Release files for single-cartpole-custom-gym-env 1.2.5
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| single_cartpole_custom_gym_env-1.2.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 16.9 kB
Release files / single_cartpole_custom_gym_env-1.2.5.tar.gz
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Release files / single_cartpole_custom_gym_env-1.2.5-py3-none-any.whl
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