aasseman/distributed-evolutionary-ml

A tool for experimenting with evolutionary optimization methods for machine learning algorithms, by distributing the workload over a large number of compute nodes on the IBM Cloud. For now, it only includes an implementation of [Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning](https://arxiv.org/abs/1712.06567).

PythonApache-2.0