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Reinforcement-Learning-Environments

This repository is dedicated to custom environments and agents for Reinforcement Learning (RL) research and development. It focuses on building flexible and efficient RL environments using frameworks like OpenAI Gym and Stable Baselines, as well as implementing various RL algorithms.

Topics

  • Custom RL Environments
  • Deep Reinforcement Learning Algorithms
  • Multi-Agent Systems
  • Simulation and Game Theory

Installation

# Clone the repository
git clone https://github.com/Whilly3/Reinforcement-Learning-Environments.git
cd Reinforcement-Learning-Environments

# Install dependencies
pip install -r requirements.txt

Usage

Each environment and agent implementation will have its own dedicated directory with detailed usage instructions and examples.

Contribution

Contributions are highly encouraged! Please refer to the contribution guidelines for details on how to get involved.

License

This project is licensed under the MIT License.

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Custom environments and agents for Reinforcement Learning research and development, implemented in Python with frameworks like OpenAI Gym and Stable Baselines.

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