This is a very simple illustration of artificial neural nets with genetic algorithms.

the project consist of 3 classes:

• Position
• NeutalNet
• AI

#Position: describe a simple position of snake game consisting of snake and a randomly generated food

#NeuralNet: Basic neural net class for:

• compute an activation from an input
• mutate the net
• compute cross-over of two nets

#AI: given a neural net it choses the best direction to go

when running program 3 options are possibles: #init create the first generation and save it to files candidate0..9.nn

#simulation perform simulation to iteratively find the best candidates that have the best fitness using a genetic algorithm

#test test candidate0.nn performance

two tests are available:

• learning xor
• learning how to eat food without touching walls you can use xor test by setting XOR_TEST to true you can use snake game by setting it to false

#Build

install cmake and build-essentials $sudo apt-get install cmake build-essentials

$cmake .

$make

#Run $./NeuralNetGeneticAlgo