neuro evollution steering 2

shiffman · shiffman · commit aa48916efe46 · 2019-04-22T12:51:19.000-04:00
diff --git a/05_neuro_evolution_steering_2/index.html b/05_neuro_evolution_steering_2/index.html
@@ -0,0 +1,29 @@
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <meta http-equiv="X-UA-Compatible" content="ie=edge" />
+    <title>NeuroEvolution Steering</title>
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.8.0/p5.min.js"></script>
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.8.0/addons/p5.dom.min.js"></script>
+    <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@1.0.4/dist/tf.min.js"></script>
+  </head>
+  <body>
+    <script src="nn.js"></script>
+    <script src="sketch.js"></script>
+    <script src="vehicle.js"></script>
+    <script src="obstacle.js"></script>
+    <div id="canvascontainer"></div>
+    <div id="interface">
+      <p>
+        speed: <input id="speedSlider" type="range" min="1" max="10" value="1"> <span id="speed">1</span>
+      </p>
+      <p>
+        debug: <input id="debug" type="checkbox"></input>
+      </p>
+    </div>
+  
+  </body>
+</html>
+
diff --git a/05_neuro_evolution_steering_2/nn.js b/05_neuro_evolution_steering_2/nn.js
@@ -0,0 +1,96 @@
+// Daniel Shiffman
+// Nature of Code
+// https://github.com/nature-of-code/noc-syllabus-S19
+
+class NeuralNetwork {
+  constructor(a, b, c, d) {
+    if (a instanceof tf.Sequential) {
+      this.model = a;
+      this.num_inputs = b;
+      this.num_hidden = c;
+      this.num_outputs = d;
+    } else {
+      this.num_inputs = a;
+      this.num_hidden = b;
+      this.num_outputs = c;
+      this.model = this.createModel();
+    }
+  }
+
+  createModel() {
+    const model = tf.sequential();
+    let hidden = tf.layers.dense({
+      inputShape: [this.num_inputs],
+      units: this.num_hidden,
+      activation: 'tanh'
+    });
+    let output = tf.layers.dense({
+      units: this.num_outputs,
+      activation: 'tanh'
+    });
+    model.add(hidden);
+    model.add(output);
+    return model;
+  }
+
+  dispose() {
+    this.model.dispose();
+  }
+
+  save() {
+    this.model.save('downloads://vehicle`-brain');
+  }
+
+  // Synchronous for now
+  predict(input_array) {
+    // console.log(input_array);
+    return tf.tidy(() => {
+      let xs = tf.tensor([input_array]);
+      let ys = this.model.predict(xs);
+      let y_values = ys.dataSync();
+      return y_values;
+    });
+  }
+
+  // Adding function for neuro-evolution
+  copy() {
+    return tf.tidy(() => {
+      const modelCopy = this.createModel();
+      const w = this.model.getWeights();
+      for (let i = 0; i < w.length; i++) {
+        w[i] = w[i].clone();
+      }
+      modelCopy.setWeights(w);
+      const nn = new NeuralNetwork(modelCopy, this.num_inputs, this.num_hidden, this.num_outputs);
+      return nn;
+    });
+  }
+
+  // Accept an arbitrary function for mutation
+  mutate(rate) {
+    tf.tidy(() => {
+      const w = this.model.getWeights();
+      for (let i = 0; i < w.length; i++) {
+        let shape = w[i].shape;
+        let arr = w[i].dataSync().slice();
+        for (let j = 0; j < arr.length; j++) {
+          arr[j] = mutateWeight(arr[j], rate);
+        }
+        let newW = tf.tensor(arr, shape);
+        w[i] = newW;
+      }
+      this.model.setWeights(w);
+    });
+  }
+}
+
+// Mutation function to be passed into bird.brain
+function mutateWeight(x, rate) {
+  if (random(1) < rate) {
+    let offset = randomGaussian() * 0.5;
+    let newx = x + offset;
+    return newx;
+  } else {
+    return x;
+  }
+}
diff --git a/05_neuro_evolution_steering_2/obstacle.js b/05_neuro_evolution_steering_2/obstacle.js
@@ -0,0 +1,16 @@
+class Obstacle {
+  constructor(x, y) {
+    this.pos = createVector(x, y);
+    this.r = 16;
+  }
+
+  update() {
+    this.pos.y += 4;
+  }
+
+  show() {
+    stroke(255);
+    noFill();
+    ellipse(this.pos.x, this.pos.y, this.r * 2);
+  }
+}
diff --git a/05_neuro_evolution_steering_2/sketch.js b/05_neuro_evolution_steering_2/sketch.js
@@ -0,0 +1,107 @@
+// Daniel Shiffman
+// Nature of Code
+// https://github.com/nature-of-code/noc-syllabus-S19
+
+// Evolutionary "Steering Behavior" Simulation
+
+// An array of vehicles
+let population = [];
+
+// An array of "obstacles"
+let obstacles = [];
+
+// Checkbox to show additional info
+let debug;
+
+// Slider to speed up simulation
+let speedSlider;
+let speedSpan;
+
+let totalVehicles = 30;
+
+let best = null;
+
+function setup() {
+  tf.setBackend('cpu');
+
+  // Add canvas and grab checkbox and slider
+  let canvas = createCanvas(640, 480);
+  canvas.parent('canvascontainer');
+  debug = select('#debug');
+  speedSlider = select('#speedSlider');
+  speedSpan = select('#speed');
+
+  // Create initial population
+  for (let i = 0; i < totalVehicles; i++) {
+    population[i] = new Vehicle();
+  }
+}
+
+let counter = 0;
+
+function draw() {
+  background(0);
+
+  // How fast should we speed up
+  let cycles = speedSlider.value();
+  speedSpan.html(cycles);
+
+  // Variable to keep track of highest scoring vehicle
+
+  // Run the simulation "cycles" amount of time
+  for (let n = 0; n < cycles; n++) {
+    // Always keep a minimum amount of food
+    if ((frameCount * cycles + n) % 15 == 0) {
+      obstacles.push(new Obstacle(random(-50, width), 0));
+    }
+
+    let record = -1;
+    // Go through all vehicles and find the best!
+    for (let i = population.length - 1; i >= 0; i--) {
+      let v = population[i];
+      v.update();
+      const dead = v.check(obstacles);
+      // If the vehicle has died, remove
+      if (dead) {
+        population.splice(i, 1);
+      } else {
+        // Is it the vehicles that has lived the longest?
+        if (v.score > record) {
+          record = v.score;
+          best = v;
+        }
+      }
+    }
+
+    // If there is less than 20 apply reproduction
+    while (population.length < 20) {
+      for (let v of population) {
+        // Every vehicle has a chance of cloning itself according to score
+        // Argument to "clone" is probability
+        let newVehicle = v.clone((0.1 * v.score) / record);
+        // If there is a child
+        if (newVehicle != null) {
+          population.push(newVehicle);
+        }
+      }
+    }
+
+    for (let i = 0; i < obstacles.length; i++) {
+      obstacles[i].update();
+    }
+  }
+
+  // Draw all the food
+  for (let i = 0; i < obstacles.length; i++) {
+    obstacles[i].show();
+  }
+
+  best.highlight();
+
+  // Draw all the vehicles
+  if (debug.checked()) {
+    for (let v of population) {
+      v.debug();
+    }
+  }
+}
diff --git a/05_neuro_evolution_steering_2/vehicle.js b/05_neuro_evolution_steering_2/vehicle.js
