evo-NEAT

A Kotlin implementation of NEAT(NeuroEvolution of Augmenting Topologies ) for the generation of evolving artificial neural networks with Coroutines support.

Implimentation of http://nn.cs.utexas.edu/downloads/papers/stanley.ec02.pdf

Usage

Add it in your root build.gradle at the end of repositories:

allprojects {
	repositories {
		...
		maven { url 'https://jitpack.io' }
	}
}

Step 2. Add the dependency

dependencies {
        implementation 'com.github.Advice-Dog:evo-NEAT:-SNAPSHOT'
}

Implementation

You must implement the Environment interface and override the evaluateFitness(population: List<Genome>) function.

For each Genome in the population, you want to call Genome.evaluateNetwork(...) with your inputs, and then calculate the fitness from the result and set it on the Genome.

Config

You can config how the model is created using the NEATConfig.Builder.

val config: NeatConfig = NEATConfig.Builder()
    .setPopulationSize(300)
    .setBatchSize(100)
    .setInputs(2)
    .setOutputs(1)
    .build()

Coroutines

For each generation, the library will separate them into batches and calculate their fitness in parallel. The number of Coroutines is based on the population size / the batch size.

With the following config, the library will create 10 Coroutines each generation.

val config: NeatConfig = NEATConfig.Builder()
    .setPopulationSize(500)
    .setBatchSize(50)
.build()

Example

A full example of the XOR implementation is given in the folder evo-NEAT/src/examples/ .