deatf 0.1

Distributed Evolutionary Algorithms in TensorFlow (DEATF) is a framework where networks generated with TensorFlow are evolved via DEAP.

DEATF

Distributed Evolutionary Algorithms in TensorFlow (DEATF) is a framework where networks generated with TensorFlow [1] are evolved via DEAP [2]. DEATF is a framework directly based in EvoFlow [3] framework created by Unai Garciarena.

Installation

Requirements

Example

References

[1] Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., ... & Ghemawat, S. (2016). Tensorflow: Large-scale machine learning on heterogeneous distributed systems. arXiv preprint arXiv:1603.04467.

[2] Fortin, F. A., Rainville, F. M. D., Gardner, M. A., Parizeau, M., & Gagné, C. (2012). DEAP: Evolutionary algorithms made easy. Journal of Machine Learning Research, 13(Jul), 2171-2175.

[3] Garciarena, U., Santana, R., & Mendiburu, A. (2018, July). Evolved GANs for generating Pareto set approximations. In Proceedings of the Genetic and Evolutionary Computation Conference (pp. 434-441). ACM.