Quantum Reinforcement Learning library: environments, policies and training loops with PennyLane.
Project description
QRL-QAI
The open-source library for Quantum Reinforcement Learning
QRL-QAI is a Python framework built to serve as a central platform for everything quantum reinforcement learning.
Built on top of Gymnasium, PennyLane, and PyTorch, this package provides the tools you need to explore and develop Quantum AI.
📑 Table of Contents
✨ Key Features
- Native Quantum Environments – Train and test your agents on quantum-specific environments.
- A Unified Platform – Compare quantum agents with classical agents fairly in one framework.
- Simplified Abstractions – Work with quantum circuits and environments using clean, intuitive APIs.
🗺 Roadmap
🚀 Getting Started
Install the package directly from PyPI:
pip install qrl-qai
🧠 Core Algorithms
Cross-Entropy Method (CEM)
📚 References
Deep Reinforcement Learning Hands-On (Third Edition) by Maxim Lapan.
🤝 Contributing
Contributions are welcome! 🎉
See our CONTRIBUTING.md for guidelines.
📜 License
This project is licensed under the Apache 2.0 License
📬 Contact
Initiated by Jay Shah
Email: jay.shah@qrlqai.com
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