# NEAT
Genetic Algorithm for Artificial Neural Networks

# NEAT
Genetic Algorithm for Artificial Neural Networks

This is an implamenation of a customized and more flexible C++ version of NEAT. It is important that credit must be given to the paper that this is based on. This is a C++ implamentation of the system described in [this](http://www.mitpressjournals.org/doi/abs/10.1162/106365602320169811) article. This project attempts to be a simple but efficient implamentation of the core ideas that are stated in the orriginal paper that can be easily scaled and used in whatever machine learning problems may require it. The implamentation will allow for a purely genetic version of the neural network optimization process to be used (as stated in the paper) but will also allow for a backpropogation method of learning on evolved structure. This means this implamentation can be used for both supervised and reinforcement type learning problems.


Sources and Resources used:
-[NEAT](http://www.mitpressjournals.org/doi/abs/10.1162/106365602320169811)
-[Backpropagation example](https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/)
-[SFML](https://www.sfml-dev.org/)

Update readme so it gives credit to sources used.
Update readme so it gives credit to sources used.