NeuralNet

const numCircles = 10;

const circleRadius = 20;

const circleMaxSpeed = 5;

const numSquares = 5;

const squareSize = 30;

const numHiddenNodes = 10;

const learningRate = 0.1;

​

let circles = [];

let squares = [];

​

function setup() {

  createCanvas(800, 800);

​

  // Initialize circles

  for (let i = 0; i < numCircles; i++) {

    circles.push(new Circle());

  }

​

  // Initialize squares

  for (let i = 0; i < numSquares; i++) {

    let neuralNetwork = new NeuralNetwork(numCircles * 2, numHiddenNodes, 4);

    squares.push(new Square(neuralNetwork));

  }

}

​

function draw() {

  background(220);

​

  // Move circles

  for (let i = 0; i < numCircles; i++) {

    circles[i].move();

    circles[i].display();

  }

​

  // Update squares

  for (let i = 0; i < squares.length; i++) {

    squares[i].update();

    squares[i].display();

  }

  life();

}

​

function life() {

  // Train neural network on key press

    let newSquares = [];

    let indexRemoval = [];

    for (let i = 0; i < numSquares; i++) {

      //print(squares[i]);

      if(squares[i].energy < 1){

        if(squares[i].score >= 1){

          let neurn = squares[i].neuralNetwork;

          neurn.mutateNodes();

          newSquares.push(new Square(neurn));

          newSquares.push(new Square(neurn));

          indexRemoval.push(i);

        }

        else{

          let neuralNetwork = new NeuralNetwork(numCircles * 2, numHiddenNodes, 4);

          squares.splice(i,1,new Square(neuralNetwork));

        }

      }

    }

    for (let i = 0; i < indexRemoval.length; i++) {

      squares.splice(indexRemoval[i],1);

    }

    for (let i = 0; i < newSquares.length; i++) {

      squares.push(newSquares[i]);

    }

}