minor improvements

Author: shiffman

examples/NeuroEvolution-flappy-bird/bird.js

@@ -5,7 +5,7 @@ class Bird {
       this.brain = brain;
     } else {
       this.brain = ml5.neuralNetwork({
-        inputs: 5,
+        inputs: 4,
         outputs: ["flap", "no flap"],
         task: "classification",
         neuroEvolution: true,
@@ -29,7 +29,7 @@ class Bird {
   think(pipes) {
     let nextPipe = null;
     for (let pipe of pipes) {
-      if (pipe.x > this.x) {
+      if (pipe.x + pipe.w > this.x) {
         nextPipe = pipe;
         break;
       }
@@ -39,7 +39,6 @@ class Bird {
       this.y / height,
       this.velocity / height,
       nextPipe.top / height,
-      nextPipe.bottom / height,
       (nextPipe.x - this.x) / width,
     ];
 
@@ -59,12 +58,11 @@ class Bird {
     this.velocity += this.gravity;
     this.y += this.velocity;
     // Dampen velocity
-    this.velocity *= 0.9;
+    this.velocity *= 0.95;
 
     // Handle the "floor"
-    if (this.y > height) {
-      this.y = height;
-      this.velocity = 0;
+    if (this.y > height || this.y < 0) {
+      this.alive = false;
     }
 
     this.fitness++;

examples/NeuroEvolution-flappy-bird/pipe.js

@@ -1,6 +1,6 @@
 class Pipe {
   constructor() {
-    this.spacing = 75;
+    this.spacing = 100;
     this.top = random(height - this.spacing);
     this.bottom = this.top + this.spacing;
     this.x = width;

examples/NeuroEvolution-flappy-bird/sketch.js

@@ -15,8 +15,8 @@ function draw() {
   background(255);
 
   for (let i = pipes.length - 1; i >= 0; i--) {
-    pipes[i].show();
     pipes[i].update();
+    pipes[i].show();
     if (pipes[i].offscreen()) {
       pipes.splice(i, 1);
     }
@@ -35,15 +35,13 @@ function draw() {
     }
   }
 
-  if (frameCount % 75 == 0) {
+  if (frameCount % 100 == 0) {
     pipes.push(new Pipe());
   }
 
   if (allBirdsDead()) {
     normalizeFitness();
     reproduction();
-    pipes = [];
-    pipes.push(new Pipe());
   }
 }
 
@@ -62,7 +60,7 @@ function reproduction() {
     let parentA = weightedSelection();
     let parentB = weightedSelection();
     let child = parentA.brain.crossover(parentB.brain);
-    child.mutate(0.1);
+    child.mutate(0.01);
     nextBirds[i] = new Bird(child);
   }
   birds = nextBirds;