Skip to content
/ dsrl Public
forked from mahmoudakl/dsrl

Deep Spiking Reinforcement Learning

Notifications You must be signed in to change notification settings

metr0jw/dsrl

 
 

Repository files navigation

Deep Spiking Reinforcement Learning

Implementations of Deep Reinforcement Learning (DRL) algorithms with Spiking Neural Netowrks (SNNs) in PyTorch. SNNs are based on the SpyTorch implementations, with custom encoding and decoding mechanisms.

Dependency installation

Tested on Ubuntu 20.04 and Python 3.8.12. Creating a virtual environment is recommended.

pip install -r requirements.txt

For MuJoCo based environments (Ant-v3, HalfCheetah-v3, and Hopper-v3), install MuJoCo as described here.

Citation

If you use our code, please consider citing our research:

@ARTICLE{10.3389/fnbot.2022.1075647,
AUTHOR={Akl, Mahmoud and Ergene, Deniz and Walter, Florian and Knoll, Alois},   
TITLE={Toward robust and scalable deep spiking reinforcement learning},      
JOURNAL={Frontiers in Neurorobotics},      
VOLUME={16},           
YEAR={2023},      
URL={https://www.frontiersin.org/articles/10.3389/fnbot.2022.1075647},       
DOI={10.3389/fnbot.2022.1075647},      
ISSN={1662-5218},   
}
@inproceedings{10.1145/3546790.3546804,
author = {Akl, Mahmoud and Sandamirskaya, Yulia and Ergene, Deniz and Walter, Florian and Knoll, Alois},
title = {Fine-Tuning Deep Reinforcement Learning Policies with r-STDP for Domain Adaptation},
year = {2022},
isbn = {9781450397896},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3546790.3546804},
doi = {10.1145/3546790.3546804},
booktitle = {Proceedings of the International Conference on Neuromorphic Systems 2022},
articleno = {14},
numpages = {8},
keywords = {neural networks, spiking neural networks, reinforcement learning},
location = {Knoxville, TN, USA},
series = {ICONS '22}
}
@inproceedings{10.1145/3477145.3477159,
author = {Akl, Mahmoud and Sandamirskaya, Yulia and Walter, Florian and Knoll, Alois},
title = {Porting Deep Spiking Q-Networks to Neuromorphic Chip Loihi},
year = {2021},
isbn = {9781450386913},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3477145.3477159},
doi = {10.1145/3477145.3477159},
booktitle = {International Conference on Neuromorphic Systems 2021},
articleno = {13},
numpages = {7},
keywords = {neuromorphic hardware, reinforcement learning, Spiking neural networks},
location = {Knoxville, TN, USA},
series = {ICONS 2021}
}

About

Deep Spiking Reinforcement Learning

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 63.8%
  • Jupyter Notebook 36.2%