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shiffmanshiffman
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working neuroevolution steering example
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‎examples/NeuroEvolution-steering/index.html‎

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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8" />
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<meta http-equiv="X-UA-Compatible" content="IE=edge" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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<title>ml5.js NeuroEvolution Steering</title>
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<script src="p5.min.js"></script>
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<script src="../../dist/ml5.js"></script>
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</head>
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<body>
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<script src="vehicle.js"></script>
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<script src="sketch.js"></script>
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</body>
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</html>

‎examples/NeuroEvolution-steering/p5.min.js‎

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‎examples/NeuroEvolution-steering/sketch.js‎

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let vehicles = [];
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let timeSlider;
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let lifetime = 0;
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let target;
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function setup() {
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createCanvas(640, 240);
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// Initialize a set number of vehicles
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for (let i = 0; i < 50; i++) {
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vehicles[i] = new Vehicle(random(width), random(height));
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}
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ml5.tf.setBackend("cpu");
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target = createVector(random(width), random(height));
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timeSlider = createSlider(1, 20, 1);
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}
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function draw() {
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background(255);
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for (let i = 0; i < timeSlider.value(); i++) {
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for (let v of vehicles) {
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v.edges();
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v.think(target);
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v.eat(target);
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v.update();
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}
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lifetime++;
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}
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let best = null;
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let record = -1;
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for (let v of vehicles) {
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v.show();
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if (v.fitness > record) {
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record = v.fitness;
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best = v;
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}
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}
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best.show();
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noStroke();
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fill(255, 0, 0, 100);
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circle(best.position.x, best.position.y, 64);
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fill(0);
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text(best.fitness, best.position.x + 12, best.position.y);
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fill(0, 0, 255, 100);
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circle(target.x, target.y, 32);
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stroke(0, 100);
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strokeWeight(1);
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//line(target.x, target.y, best.position.x, best.position.y);
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if (lifetime > 500) {
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normalizeFitness();
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reproduction();
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target = createVector(random(width), random(height));
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lifetime = 0;
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}
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// if (allVehiclesDead()) {
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// }
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fill(0);
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text(lifetime, 10, 30);
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}
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// function allVehiclesDead() {
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// for (let v of vehicles) {
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// if (v.alive) {
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// return false;
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// }
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// }
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// return true;
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// }
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function normalizeFitness() {
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let recordFitness = 0;
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for (let v of vehicles) {
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if (v.fitness > recordFitness) {
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recordFitness = v.fitness;
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}
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v.fitness = pow(2, v.fitness);
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}
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console.log(recordFitness);
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let sum = 0;
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for (let v of vehicles) {
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sum += v.fitness;
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}
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for (let v of vehicles) {
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v.fitness = v.fitness / sum;
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}
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}
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function reproduction() {
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let nextVehicles = [];
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for (let i = 0; i < vehicles.length; i++) {
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let parentA = weightedSelection();
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let parentB = weightedSelection();
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let child = parentA.crossover(parentB);
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child.mutate(0.1);
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nextVehicles[i] = new Vehicle(random(width), random(height), child);
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}
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vehicles = nextVehicles;
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}
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function weightedSelection() {
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let index = 0;
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let start = random(1);
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while (start > 0) {
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start = start - vehicles[index].fitness;
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index++;
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}
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index--;
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return vehicles[index].brain;
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}

‎examples/NeuroEvolution-steering/vehicle.js‎

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class Vehicle {
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constructor(x, y, brain) {
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this.position = createVector(x, y);
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this.velocity = createVector(0, 0);
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this.acceleration = createVector(0, 0);
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this.r = 4;
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this.maxspeed = 4;
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this.fitness = 0;
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if (brain) {
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this.brain = brain;
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} else {
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this.brain = ml5.neuralNetwork({
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inputs: 2,
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outputs: 2,
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task: "regression",
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neuroEvolution: true,
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});
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}
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}
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eat(food) {
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let d = p5.Vector.dist(this.position, food);
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if (d < 10) {
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this.fitness++;
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// this.position = createVector(random(width), random(height));
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target = createVector(random(width), random(height));
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}
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}
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think(food) {
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let v = p5.Vector.sub(food, this.position);
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v.normalize();
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let inputs = [v.x, v.y];
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// Predicting the force to apply
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const outputs = this.brain.predictSync(inputs);
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// let x = 2 * outputs[0].value - 1;
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// let y = 2 * outputs[1].value - 1;
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// let force = createVector(x, y); //.setMag(magnitude);
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// force.setMag(1);
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let angle = outputs[0].value * TWO_PI;
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let magnitude = outputs[1].value;
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let force = p5.Vector.fromAngle(angle).setMag(magnitude);
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this.applyForce(force);
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}
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// Method to update location
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update() {
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// Update velocity
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this.velocity.add(this.acceleration);
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// Limit speed
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this.velocity.limit(this.maxspeed);
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this.position.add(this.velocity);
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// Reset acceleration to 0 each cycle
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this.acceleration.mult(0);
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// if (
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// this.position.x > width ||
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// this.position.y > height ||
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// this.position.x < 0 ||
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// this.position.y < 0
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// ) {
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// this.alive = false;
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// }
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}
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applyForce(force) {
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// We could add mass here if we want A = F / M
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this.acceleration.add(force);
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}
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// Wraparound
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edges() {
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// this.position.x = constrain(this.position.x, 0, width);
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// this.position.y = constrain(this.position.y, 0, height);
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//if (this.position.x < -this.r) this.position.x = width + this.r;
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//if (this.position.y < -this.r) this.position.y = height + this.r;
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//if (this.position.x > width + this.r) this.position.x = -this.r;
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//if (this.position.y > height + this.r) this.position.y = -this.r;
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}
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show() {
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//{!1} Vehicle is a triangle pointing in the direction of velocity
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let angle = this.velocity.heading();
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fill(127);
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stroke(0);
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push();
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translate(this.position.x, this.position.y);
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rotate(angle);
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beginShape();
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vertex(this.r * 2, 0);
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vertex(-this.r * 2, -this.r);
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vertex(-this.r * 2, this.r);
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endShape(CLOSE);
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pop();
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//fill(0);
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//noStroke();
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//text(this.fitness, this.position.x + 12, this.position.y);
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// let d = p5.Vector.dist(this.position, this.target);
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// if (d < 50) {
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// stroke(0, 200);
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// strokeWeight(1);
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// line(this.position.x, this.position.y, this.target.x, this.target.y);
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// fill(0, 255, 0, 100);
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// circle(this.target.x, this.target.y, 8);
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//}
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}
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}

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