new neuroevolution regression path example

ml5js · Apr 16, 2020 · 8d74aa0 · 8d74aa0
1 parent ecf09a1
commit 8d74aa0
Show file tree

Hide file tree

Showing 4 changed files with 234 additions and 0 deletions.
diff --git a/examples/p5js/NeuralNetwork/NeuroEvolution_Path/index.html b/examples/p5js/NeuralNetwork/NeuroEvolution_Path/index.html
@@ -0,0 +1,16 @@
+<!DOCTYPE html>
+<html>
+
+<head>
+ <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.10.2/p5.min.js"></script>
+ <script src="http:https://localhost:8080/ml5.js" type="text/javascript"></script>
+ <meta charset="utf-8" />
+</head>
+
+<body>
+ <script src="population.js"></script>
+ <script src="particle.js"></script>
+ <script src="sketch.js"></script>
+</body>
+
+</html>
diff --git a/examples/p5js/NeuralNetwork/NeuroEvolution_Path/particle.js b/examples/p5js/NeuralNetwork/NeuroEvolution_Path/particle.js
@@ -0,0 +1,67 @@
+// The Nature of Code
+// Daniel Shiffman
+// http:https://natureofcode.com
+
+class Particle {
+ constructor(brain) {
+ // All of our physics stuff
+ this.position = createVector(width/2, height/2);
+ this.acceleration = createVector();
+ this.velocity = createVector();
+ // Fitness and DNA
+ this.fitness = 0;
+ // Bird can be created with an existing neural network
+ if (brain) {
+ this.brain = brain;
+ } else {
+ // Create a new neural network
+ const options = {
+ inputs: 2,
+ outputs: 2,
+ task: 'regression',
+ noTraining: true
+ } 
+ this.brain = ml5.neuralNetwork(options);
+ this.brain.mutate(1);
+ }
+ }
+
+ // fitness = one divided by distance squared
+ calcFitness() {
+ let d = p5.Vector.dist(this.position, target);
+ this.fitness = pow(1 / d, 2);
+ return this.fitness;
+ }
+
+ applyForce(force) {
+ this.acceleration.add(force);
+ }
+
+ // Run in relation to all the obstacles
+ // If I'm stuck, don't bother updating or checking for intersection
+ think() {
+ let inputs = [];
+ inputs[0] = this.position.x / width;
+ inputs[1] = this.position.y / height;
+ let outputs = this.brain.predictSync(inputs);
+ this.velocity = p5.Vector.fromAngle(outputs[0].value * TWO_PI);
+ this.velocity.mult(outputs[1].value * 5);
+
+ // let force = p5.Vector.fromAngle(angle);
+ // force.mult(mag);
+ // this.applyForce(force);
+ }
+
+
+ update() {
+ this.velocity.add(this.acceleration);
+ this.position.add(this.velocity);
+ this.acceleration.mult(0);
+ }
+
+ show() {
+ stroke(255);
+ fill(255, 150);
+ ellipse(this.position.x, this.position.y, 8);
+ }
+}
diff --git a/examples/p5js/NeuralNetwork/NeuroEvolution_Path/population.js b/examples/p5js/NeuralNetwork/NeuroEvolution_Path/population.js
@@ -0,0 +1,72 @@
+// The Nature of Code
+// Daniel Shiffman
+// http:https://natureofcode.com
+
+
+// A class to describe a population of particles
+
+class Population {
+ constructor(total) {
+ this.population = [];
+ this.generations = 0; // Number of generations
+ for (let i = 0; i < total; i++) {
+ this.population[i] = new Particle();
+ }
+ }
+
+ update() {
+ for (let p of this.population) {
+ p.think();
+ p.update();
+ }
+ }
+
+ show() {
+ for (let p of this.population) {
+ p.show();
+ }
+ }
+
+ reproduce() {
+ let brainA = this.pickOne();
+ let brainB = this.pickOne();
+ let childBrain = brainA.crossover(brainB);
+ // 1% mutation rate
+ childBrain.mutate(0.01);
+ return new Particle(childBrain);
+ }
+
+ // Pick one parent probability according to normalized fitness
+ pickOne() {
+ let index = 0;
+ let r = random(1);
+ while (r > 0) {
+ r = r - this.population[index].fitness;
+ index++;
+ }
+ index--;
+ return this.population[index].brain;
+ }
+
+ // Normalize all fitness values
+ calculateFitness() {
+ let sum = 0;
+ for (let p of this.population) {
+ sum += p.calcFitness();
+ }
+ for (let p of this.population) {
+ p.fitness = p.fitness / sum;
+ }
+ }
+
+ // Making the next generation
+ reproduction() {
+ let nextPopulation = [];
+ // Refill the population with children from the mating pool
+ for (let i = 0; i < this.population.length; i++) {
+ nextPopulation[i] = this.reproduce();
+ }
+ this.population = nextPopulation;
+ this.generations++;
+ }
+}
diff --git a/examples/p5js/NeuralNetwork/NeuroEvolution_Path/sketch.js b/examples/p5js/NeuralNetwork/NeuroEvolution_Path/sketch.js
@@ -0,0 +1,79 @@
+// The Nature of Code
+// Daniel Shiffman
+// http:https://natureofcode.com
+
+
+// How long should each generation live
+let lifetime; 
+let lifeCounter;
+
+// Population
+let population; 
+
+// Target position
+let target; 
+
+// Interface
+let info;
+let slider;
+
+function setup() {
+ let canvas = createCanvas(600, 600);
+
+ // Move the target if you click on the canvas
+ canvas.mousePressed(function() {
+ target.x = mouseX;
+ target.y = mouseY; 
+ });
+
+ // Improve performance for many small neural networks
+ ml5.tf.setBackend('cpu');
+
+ // The number of cycles we will allow a generation to live
+ lifetime = 200;
+ lifeCounter = 0;
+
+
+ // Arbitrary starting target
+ target = createVector(20, height / 2);
+
+ // Create a population N Particles
+ population = new Population(100);
+
+ // Interface
+ info = createP("");
+ // Slider for speeding up simulation
+ slider = createSlider(1, 50, 1);
+
+}
+
+function draw() {
+
+ // Update the population
+ for (let n = 0; n < slider.value(); n++) {
+ if (lifeCounter < lifetime) {
+ population.update();
+ lifeCounter++;
+ // Otherwise a new generation
+ } else {
+ lifeCounter = 0;
+ // Next generation
+ population.calculateFitness();
+ population.reproduction();
+ }
+
+ }
+
+ // Draw target
+ background(0);
+ fill(100, 255, 100);
+ stroke(255);
+ rectMode(CENTER);
+ rect(target.x, target.y, 24, 24);
+
+ // Show population
+ population.show();
+
+ // Display some info
+ info.html(`Generation # ${population.generations}<br>Cycles left: ${(lifetime - lifeCounter)}`);
+}