Welcome to the stellar world of the Q Algorithm*! This project explores the depths of reinforcement learning through the lens of Q-learning, a fundamental technique in training intelligent agents. As a night owl and cosmic coder, I’ve poured my passion into crafting an implementation that’s as insightful as it is innovative.
Q* is a state-of-the-art approach to reinforcement learning, focusing on optimizing the Q-values in decision-making processes. It enables agents to learn optimal actions by exploring environments and receiving rewards, making it a cornerstone of AI in dynamic settings.
- Enhanced Q-Learning: Building upon traditional Q-learning with advanced techniques for faster convergence and better performance.
- Versatile Applications: Suitable for a range of environments, from grid worlds to more complex simulations.
- Visualization Tools: Includes tools to visualize learning progress and agent behavior, giving you a window into the AI’s journey through the universe of decision-making.
To get started with Q*, follow these cosmic steps:
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Clone the Repository:
git clone https://github.com/TheHelloWorldMe/q-star-algorithm.git
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Navigate to the Project Directory:
cd q-star-algorithm -
Install Dependencies:
pip install -r requirements.txt
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Run the Q Algorithm*:
python q_star_algorithm.py
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Customize Parameters: Adjust hyperparameters in
config.yamlto explore different configurations and see how they impact the agent’s learning. -
Visualize Results: Use the provided scripts in the
visualizationdirectory to generate plots and insights into the agent’s performance.
Check out the examples/ folder for pre-configured environments and examples demonstrating the Q* algorithm in action. These include:
- Grid World: A classic environment to see Q* in a simple, understandable context.
- Maze Navigation: Test the algorithm’s prowess in solving complex mazes.
Feel inspired to add your own stardust? Contributions are welcome! Whether it’s a new feature, an improvement, or just a bug fix, your help is appreciated. Please review the CONTRIBUTING.md for guidelines on how to get involved.
This project is licensed under the MIT License. Feel free to explore, adapt, and contribute to this cosmic endeavor.
Join me in exploring the universe of reinforcement learning with Q. Together, let’s push the boundaries of AI and discover new horizons.*
Keep coding, keep exploring, and let the stars be your guide. 🌟