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Code Issues Releases Wiki Activity

implemented brains

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This commit is contained in:
Enrico Fasoli 2015-06-28 22:52:32 +02:00
parent 7c99c1075e
commit 7203371f2e
7 changed files with 226 additions and 38 deletions

9
.nb-gradle/profiles/private/aux-config
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@ -8,7 +8,14 @@
</open-files>
<editor-bookmarks lastBookmarkId="0" xmlns="http://www.netbeans.org/ns/editor-bookmarks/2"/>
<open-files xmlns="http://www.netbeans.org/ns/projectui-open-files/2">
<group/>
<group>
<file>file:/home/fazo/Documents/Git/AIrium/core/src/logic/neural/NeuralConnection.java</file>
<file>file:/home/fazo/Documents/Git/AIrium/core/src/com/mygdx/game/Game.java</file>
<file>file:/home/fazo/Documents/Git/AIrium/core/src/logic/neural/Neuron.java</file>
<file>file:/home/fazo/Documents/Git/AIrium/core/src/logic/Creature.java</file>
<file>file:/home/fazo/Documents/Git/AIrium/core/src/logic/neural/Brain.java</file>
<file>file:/home/fazo/Documents/Git/AIrium/core/src/logic/World.java</file>
</group>
</open-files>
</auxiliary>
</gradle-project-properties>

53
core/src/logic/Creature.java
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@ -2,6 +2,7 @@ package logic;
import com.badlogic.gdx.graphics.glutils.ShapeRenderer;
import com.mygdx.game.Game;
import logic.neural.Brain;
/**
* A (hopefully) smart biological creature.
@ -11,8 +12,10 @@ import com.mygdx.game.Game;
public class Creature extends Element {
public static final int default_radius = 20;
public static final float max_speed = 3;
private float dir, speed, accel, sightRange, fov, fitness, rotSpeed;
private Brain brain;
private float dir, speed, sightRange, fov, fitness, rotSpeed;
private float hp;
private Sight sight;
@ -20,12 +23,12 @@ public class Creature extends Element {
super(x, y, default_radius);
dir = (float) (Math.random() * 2 * Math.PI);
hp = 100;
speed = (float) Math.random() * 3;
rotSpeed = (float) Math.random() - 0.5f;
accel = 0f;
speed = 0;//(float) Math.random() * 3;
rotSpeed = 0;//(float) Math.random() - 0.5f;
sightRange = 40;
fov = (float) Math.PI / 2;
fitness = 100;
brain = new Brain(3, 2, 1, 4);
}
@Override
@ -35,12 +38,11 @@ public class Creature extends Element {
if (hp < 0) {
Game.get().getWorld().getGraveyard().add(this);
}
speed += accel; // apply acceleration
if (speed > 0) {
speed -= 0.001; // attrito
if (speed > max_speed) {
speed = max_speed;
}
if (speed < 0) {
speed = 0;
if (speed < -max_speed) {
speed = -max_speed;
}
// apply speed
float xMul = (float) Math.cos(dir), yMul = (float) Math.sin(dir);
@ -48,11 +50,38 @@ public class Creature extends Element {
dir += rotSpeed;
// try eating
eat();
fitness -= 0.1;
//fitness -= 0.1;
if (dir > 2 * Math.PI) {
dir -= 2 * Math.PI;
}
sight = look();
if (dir < 0) {
dir += 2 * Math.PI;
}
sight = look(); // take a look
// feed data to brain
float[] values = new float[3];
// 0: type of sight
// 1: distance
// 2: angle
if (sight == null) {
values[0] = 0;
values[1] = 1;
values[2] = 0;
} else if (sight.getElement() instanceof Creature) {
values[0] = 1;
values[1] = sight.getDistance() / sightRange;
values[2] = sight.getAngle();
} else {
values[0] = 0.5f;
values[1] = sight.getDistance() / sightRange;
values[2] = sight.getAngle();
}
brain.input(values);
// compute behavior
float[] actions = brain.compute();
System.out.println("Accel: " + actions[0] + " Rot: " + actions[1]);
speed = actions[0]*max_speed;
rotSpeed = actions[1] - 1f;
}
@Override
@ -116,7 +145,7 @@ public class Creature extends Element {
for (Element e : Game.get().getWorld().getElements()) {
if (e instanceof Vegetable && overlaps(e)) {
e.setSize(e.getSize() - 0.1f);
hp += 0.1f;
hp ++;
fitness++;
if (hp > 100) {
hp = 100;

4
core/src/logic/World.java
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@ -25,8 +25,8 @@ public class World {
}
public void update() {
while (elements.size() < 20) {
if (Math.random() < 0.2) {
while (elements.size() < 40) {
if (Math.random() < 0.4) {
spawnCreature();
} else {
spawnVegetable();

65
core/src/logic/neural/Brain.java
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@ -1,9 +1,74 @@
package logic.neural;
import java.util.ArrayList;
/**
*
* @author fazo
*/
public class Brain {
private ArrayList<Neuron> inputs, outputs, hidden;
public Brain(int nInputs, int nOutputs, int hiddenLayers, int neuronsPerHiddenLayer) {
inputs = new ArrayList<Neuron>(nInputs);
outputs = new ArrayList<Neuron>(nOutputs);
hidden = new ArrayList<Neuron>(hiddenLayers * neuronsPerHiddenLayer);
// Create input neurons
for (int i = 0; i < nInputs; i++) {
inputs.add(new Neuron(0));
}
// popiulate hidden layers
for (int i = 0; i < hiddenLayers; i++) {
for (int j = 0; j < neuronsPerHiddenLayer; j++) {
// create neuron
Neuron n = new Neuron(i + 1);
// add connections
for (Neuron s : inputs) {
n.getInputs().add(new NeuralConnection(randWeight(), s));
}
hidden.add(n);
System.out.println("Adding Hidden Layer "+(i+1)+" Neuron "+j+" with "+inputs.size()+" inputs");
}
}
// populate output layer
for (int i = 0; i < nOutputs; i++) {
// add neuron
Neuron n = new Neuron(hiddenLayers + 1);
int conn = 0;
for (Neuron s : hidden) {
// add connections where applicable
if (s.getLayer() == hiddenLayers) {
conn++;
n.getInputs().add(new NeuralConnection(randWeight(), s));
}
}
System.out.println("Adding Output Layer Neuron "+i+" with "+conn+" inputs");
outputs.add(n);
}
}
private float randWeight(){
return (float) Math.random()*2-1f;
}
public void input(float[] values) {
for (int i = 0; i < values.length; i++) {
inputs.get(i).setOutput(values[i]);
}
}
public float[] compute() {
for (Neuron n : hidden) {
n.clearCachedValue();
}
float[] res = new float[outputs.size()];
for (int i=0;i<outputs.size();i++) {
Neuron n = outputs.get(i);
n.clearCachedValue();
res[i] = n.compute();
}
return res;
}
}

22
core/src/logic/neural/Connection.java
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@ -1,22 +0,0 @@
package logic.neural;
/**
*
* @author fazo
*/
public class Connection {
private float weight;
public Connection(float weight) {
this.weight = weight;
}
public float getWeight() {
return weight;
}
public void setWeight(float weight) {
this.weight = weight;
}
}

44
core/src/logic/neural/NeuralConnection.java Normal file
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@ -0,0 +1,44 @@
/*
* To change this license header, choose License Headers in Project Properties.
* To change this template file, choose Tools | Templates
* and open the template in the editor.
*/
package logic.neural;
/**
*
* @author fazo
*/
public class NeuralConnection {
private float weight = 1;
private final Neuron source;
private float cachedValue;
private boolean cachedValueValid = false;
public NeuralConnection(float weight, Neuron source) {
this.source = source;
}
public float compute() {
if (cachedValueValid) {
return cachedValue;
}
// get value from Neuron
cachedValueValid = true;
return cachedValue = source.compute() * getWeight();
}
public void clearCachedValue() {
cachedValueValid = false;
}
public float getWeight() {
return weight;
}
public void setWeight(float weight) {
this.weight = weight;
}
}

67
core/src/logic/neural/Neuron.java
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@ -12,5 +12,70 @@ import java.util.ArrayList;
* @author fazo
*/
public class Neuron {
private ArrayList<Connection> inputs, outputs;
private ArrayList<NeuralConnection> inputs;
private float bias, output;
private boolean isInputNeuron;
private int layer;
private float cachedValue;
private boolean cachedValueValid = false;
public Neuron(int layer) {
this.layer = layer;
inputs = new ArrayList<NeuralConnection>();
}
public float compute() {
if (isInputNeuron) {
return output;
}
if (cachedValueValid) {
return cachedValue;
}
float a = bias * -1; // activation
for (NeuralConnection i : inputs) {
a += i.compute();
}
System.out.println("Computed Value "+a+" for neuron");
cachedValueValid = true;
// sigmoid function
cachedValue = (float) (1 / (1 + Math.pow(Math.E, a * -1)));
System.out.println("Computed Value "+cachedValue+" for neuron");
return cachedValue;
}
public void setOutput(float output) {
isInputNeuron = true;
this.output = output;
}
public ArrayList<NeuralConnection> getInputs() {
return inputs;
}
public float getBias() {
return bias;
}
public void setBias(float bias) {
this.bias = bias;
}
public boolean isIsInputNeuron() {
return isInputNeuron;
}
public int getLayer() {
return layer;
}
public void setLayer(int layer) {
this.layer = layer;
}
public void clearCachedValue() {
cachedValueValid = false;
for(NeuralConnection n : inputs) n.clearCachedValue();
}
}