news-vt/eqmarl

This is the repository for the paper "eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels" published in ICLR 2025

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This project provides an implementation of Entangled Quantum Multi-Agent Reinforcement Learning (eQMARL). It helps researchers and practitioners in quantum computing and AI explore how quantum entanglement can enhance cooperation among multiple AI agents in distributed settings. You can input various experiment configurations to simulate quantum multi-agent scenarios and analyze the performance of entangled agents.

No commits in the last 6 months.

Use this if you are a researcher or advanced practitioner experimenting with quantum machine learning and multi-agent systems to improve cooperative AI.

Not ideal if you are looking for a plug-and-play solution for classical reinforcement learning problems or do not have a strong background in quantum computing concepts.

quantum-machine-learning multi-agent-systems distributed-cooperation quantum-reinforcement-learning quantum-computing-research
Stale 6m No Package No Dependents
Maintenance 2 / 25
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Language

Jupyter Notebook

License

CC-BY-4.0

Last pushed

Oct 06, 2025

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