EvoDynamic seeks to evolve and develop suitable discrete dynamic models of self-organizing systems based on local interactions.
Installing EvoDynamic:
git clone https://github.com/SocratesNFR/EvoDynamic.git
export PYTHONPATH="/path/to/EvoDynamic":$PYTHONPATH
Dependencies used:
- Python 3.6.8
- TensorFlow 2.2.0
- Numpy 1.18.1
- Matplotlib 3.1.1
- Pillow 6.2.1
- powerlaw 1.4.6
If you use EvoDynamic for academic research, please cite the following paper:
@article{pontes2020neuro,
title={A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality},
author={Pontes-Filho, Sidney and Lind, Pedro and Yazidi, Anis and Zhang, Jianhua and Hammer, Hugo and Mello, Gustavo BM and Sandvig, Ioanna and Tufte, Gunnar and Nichele, Stefano},
journal={Cognitive Neurodynamics},
pages={1--18},
year={2020},
publisher={Springer}
}
- Pontes-Filho, Sidney, et al. "EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality." International Conference on the Applications of Evolutionary Computation (Part of EvoStar). Springer, Cham, 2020.
- Pontes-Filho, Sidney, et al. "A general representation of dynamical systems for reservoir computing." arXiv preprint arXiv:1907.01856 (2019).
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