Welcome to the AWS DeepRacer Autonomous Racing Model repository! This project provides an implementation of an autonomous racing model designed to optimize performance on the AWS DeepRacer track using reinforcement learning.
- Reinforcement Learning: Utilizes state-of-the-art reinforcement learning algorithms to train the model for optimal racing strategies. 📈
- Custom Reward Functions: Easily define and implement custom reward functions to enhance model behavior for specific racing scenarios. 🎯
- Training on AWS: Leverage the power of AWS services for scalable training and evaluation of your racing models. ☁️
- Simulation and Evaluation: Test your model in a simulated environment before deploying it on the physical DeepRacer car. 🏁
We welcome contributions to enhance the AWS DeepRacer Autonomous Racing Model! If you have ideas, bug fixes, or new features:
Fork the repository. Make your changes and add your contributions. Submit a pull request for review. Let’s accelerate our models together! 🎉
This project is intended for educational purposes. Ensure compliance with AWS usage policies and guidelines when utilizing AWS resources.
This project is licensed under the MIT License. See the LICENSE file for more details.
If you have any questions or issues, feel free to open an issue in the repository. We’re here to help! 😊
Happy Racing! 🏎️💨