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Variational Quantum Circuits for Deep Reinforcement Learning since 2019. Xanadu Quantum Software Competition 1st Prize 2019.

Home Page: https://www.sycchen.com/

License: Apache License 2.0

Python 100.00%
quantum-computing quantum-algorithms deep-learning deep-reinforcement-learning variational-quantum-circuits quantum-machine-learning quantum-information reinforcement-learning reinforcement-learning-agent pytorch

var-quantumcircuits-deeprl's Introduction

Variational-Quantum-Circuits-DeepReinforcementLearning

NEWS We start a non-commericial interview series: a first talk with Sam and his experience working VQC-DRL since 2018.

Feel free to check the videos, if you are interested in the stories behind. Part 1 Video and Part 2 Video.

This is the numerical code for the article:
Variational Quantum Circuits for Deep Reinforcement Learning (first released in Aug. 2019)

  • This work awarded the Xanadu AI software competition 2019 research track first prize. News

We also sincerely thank the supports from Xanadu AI to provide PennyLane, which is a great value to the quantum AI community.

Requirements

with pip/conda install

pennylane
pytorch
matplotlib
qiskit
gym
numpy

Run Code

  • OpenAI Frozen Lake (please also refer to the parameters )
python Code/QML_DQN_FROZEN_LAKE.py
  • Cognitive Radio Game (network-simulator 3 style)
python Code/QML_DQN_NS3.py

References

If you find this work helps your research or use the code, please consider to cite our official reference. Thank you.

@article{chen2020variational,
  title={Variational quantum circuits for deep reinforcement learning},
  author={Chen, Samuel Yen-Chi and Yang, Chao-Han Huck and Qi, Jun and Chen, Pin-Yu and Ma, Xiaoli and Goan, Hsi-Sheng},
  journal={IEEE Access},
  year={2020},
  publisher={IEEE}
}

var-quantumcircuits-deeprl's People

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amimibear avatar huckiyang avatar ycchen1989 avatar

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var-quantumcircuits-deeprl's Issues

How can I the change environment configuration for the Frozen Lake Environment?

Hello, I am working on an experiment with a different type of quantum reinforcement learning model using the same version of the Gym Frozen Lake environment that you have used in your variational quantum circuit reinforcement learning experiment. However, I am not clear on how to switch between the three different Frozen Lake configurations shown in Figure 1 of your article. If you would be willing to provide me with instructions on how to switch between the different configurations, I would really appreciate that. Thank you very much.

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