name neuroevolution example and comment

examples/p5js/NeuralNetwork/NeuroEvolution/bird.js → examples/p5js/NeuralNetwork/NeuroEvolution_FlappyBird/bird.js

@@ -1,7 +1,7 @@
 // Daniel Shiffman
-// Neuro-Evolution Flappy Bird with TensorFlow.js
-// http:https://thecodingtrain.com
-// https://youtu.be/cdUNkwXx-I4
+// Neuro-Evolution Flappy Bird with ml5.js
+
+// Bird class
 
 class Bird {
  constructor(brain) {
@@ -14,9 +14,12 @@ class Bird {
 
  this.score = 0;
  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: 5,
  outputs: ['up', 'down'],
@@ -37,7 +40,9 @@ class Bird {
  this.velocity += this.lift;
  }
 
+ // Mutate the brain
  mutate() {
+ // 10% mutation rate
  this.brain.mutate(0.1);
  }
 
@@ -53,12 +58,15 @@ class Bird {
  }
  }
 
+ // Normalize 5 inputs
  let inputs = [];
  inputs[0] = this.y / height;
  inputs[1] = closest.top / height;
  inputs[2] = closest.bottom / height;
  inputs[3] = closest.x / width;
  inputs[4] = this.velocity / 10;
+
+ // Jump according to neural network output
  const results = this.brain.classifySync(inputs);
  if (results[0].label === 'up') {
  this.up();
@@ -70,10 +78,9 @@ class Bird {
  }
 
  update() {
+ // Score increases each frame
  this.score++;
-
  this.velocity += this.gravity;
- //this.velocity *= 0.9;
  this.y += this.velocity;
  }
 }

examples/p5js/NeuralNetwork/NeuroEvolution/ga.js → examples/p5js/NeuralNetwork/NeuroEvolution_FlappyBird/ga.js

@@ -1,11 +1,16 @@
 // Daniel Shiffman
-// Neuro-Evolution Flappy Bird
+// Neuro-Evolution Flappy Bird with ml5.js
 
+// Genetic Algorithm Functions
+// TODO: create a ml5.population() class to manage this?
+
+// Create the next generation
 function nextGeneration() {
- console.log('next generation');
+console.log('next generation');
+ // Calculate fitness values
  calculateFitness();
 
- // Create a new population
+ // Create new population of birds
  for (let i = 0; i < TOTAL; i++) {
  birds[i] = reproduce();
  }
@@ -14,9 +19,11 @@ function nextGeneration() {
  for (let i = 0; i < TOTAL; i++) {
  savedBirds[i].brain.dispose();
  }
+ // Clear the array
  savedBirds = [];
 }
 
+// Create a child bird from two parents 
 function reproduce() {
  let brainA = pickOne();
  let brainB = pickOne();
@@ -25,6 +32,7 @@ function reproduce() {
  return new Bird(childBrain);
 }
 
+// Pick one parent probability according to normalized fitness
 function pickOne() {
  let index = 0;
  let r = random(1);
@@ -37,6 +45,7 @@ function pickOne() {
  return bird.brain;
 }
 
+// Normalize all fitness values
 function calculateFitness() {
  let sum = 0;
  for (let bird of savedBirds) {

examples/p5js/NeuralNetwork/NeuroEvolution/pipe.js → examples/p5js/NeuralNetwork/NeuroEvolution_FlappyBird/pipe.js

@@ -1,10 +1,11 @@
 // Daniel Shiffman
-// Neuro-Evolution Flappy Bird with TensorFlow.js
-// http:https://thecodingtrain.com
-// https://youtu.be/cdUNkwXx-I4
+// Neuro-Evolution Flappy Bird
+
+// Class for a Pipe
 
 class Pipe {
  constructor() {
+ // Fixed spacing
  this.spacing = 125;
  this.top = random(height / 6, (3 / 4) * height);
  this.bottom = height - (this.top + this.spacing);
@@ -34,10 +35,6 @@ class Pipe {
  }
 
  offscreen() {
- if (this.x < -this.w) {
- return true;
- } else {
- return false;
- }
+ return (this.x < -this.w);
  }
 }

examples/p5js/NeuralNetwork/NeuroEvolution/sketch.js → examples/p5js/NeuralNetwork/NeuroEvolution_FlappyBird/sketch.js

@@ -1,63 +1,69 @@
 // Daniel Shiffman
-// Neuro-Evolution Flappy Bird with TensorFlow.js
-// http:https://thecodingtrain.com
-// https://youtu.be/cdUNkwXx-I4
+// Neuro-Evolution Flappy Bird with ml5.js
 
 const TOTAL = 100;
+// Current birds
 let birds = [];
+// Save any birds that die
 let savedBirds = [];
 let pipes = [];
 let counter = 0;
 let slider;
 
-function keyPressed() {
- if (key === 'S') {
- let bird = birds[0];
- saveJSON(bird.brain, 'bird.json');
- }
-}
-
 function setup() {
  createCanvas(640, 480);
+ // Improves performance for small neural networks and classifySync()
  ml5.tf.setBackend('cpu');
+
+ // Slider for speeding up simulation
  slider = createSlider(1, 10, 1);
+
+ // Create initial population of birds
  for (let i = 0; i < TOTAL; i++) {
  birds[i] = new Bird();
  }
 }
 
 function draw() {
+ // Speed up simulation
  for (let n = 0; n < slider.value(); n++) {
+ // new pipes every N frames
  if (counter % 75 == 0) {
  pipes.push(new Pipe());
  }
  counter++;
 
+ // Run game
  for (let i = pipes.length - 1; i >= 0; i--) {
  pipes[i].update();
 
  for (let j = birds.length - 1; j >= 0; j--) {
  if (pipes[i].hits(birds[j])) {
+ // Save bird if it dies
  savedBirds.push(birds.splice(j, 1)[0]);
  }
  }
 
+ // Remove pipes when they leave
  if (pipes[i].offscreen()) {
  pipes.splice(i, 1);
  }
  }
 
+ // Remove / save any birds that go offscreen
  for (let i = birds.length - 1; i >= 0; i--) {
  if (birds[i].offScreen()) {
  savedBirds.push(birds.splice(i, 1)[0]);
  }
  }
 
+ // Run all birds
  for (let bird of birds) {
  bird.think(pipes);
  bird.update();
  }
 
+ // If all the birds have died go to the next generation
  if (birds.length === 0) {
  counter = 0;
  nextGeneration();
@@ -75,11 +81,4 @@ function draw() {
  for (let pipe of pipes) {
  pipe.show();
  }
-}
-
-// function keyPressed() {
-// if (key == ' ') {
-// bird.up();
-// //console.log("SPACE");
-// }
-// }
+}