Neural net learning algorithm

I have been working on making a neural network that has a goal, of hitting a moving target, it has inputs based on the distance from the shooter to the target from both axis, the rotation of the shooter, and the wind speed.

Every 5 seconds the shooter resets to a different position on the screen.

I have attempted to use a back prop algorithm, by giving calculating the error based on the distance the bullet hits from the target, and if the shooter doesn't fire a shot in the 5 second window there is also an error propagated.

My network however does not seem to be learning properly, I was wondering if anyone could point me in the right direction.

Here is my code:

import java.awt.Color; import java.awt.Graphics; import java.awt.Graphics2D; import java.util.Random; import; import javax.swing.JFrame; public class ClassMain extends JFrame{ int ShooterLocationX = 100; int ShooterLocationY = 150; int shooterDiameter = 35; int targetX = 525; int targetY = 100; int targetWidth = 15; int targetLength = 50; double error; double targetVectorX=ShooterLocationX + 100; double targetVectorY = ShooterLocationY+shooterDiameter/2; boolean direction = false; boolean ShotFired = false; boolean rotateDirection; boolean start =true; boolean shotbeenFires; double ShooterRotation = 0; double[] outputs1 = new double[4]; double[] outputs2 = new double[8]; double[] outputs3 = new double[8]; double[] outputs4 = new double[3]; Percepton[] input = new Percepton[4]; Percepton[] hidden = new Percepton[8]; Percepton[] hidden2 = new Percepton[8]; Percepton[] output = new Percepton[3]; Shooter shot = new Shooter(ShooterRotation); Random random = new Random(); long StartTime = 0; long CurrTime = 0; public static void main(String []args){ ClassMain CM= new ClassMain(); CM.setup(); } public void setup(){ setSize(900,300); setVisible(true); setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); setResizable(false); createBufferStrategy(2); repaint(); for(int i = 0; i < 4; i ++){ input[i] = new Percepton(); input[i].setInputNumber(1); } for(int i =0;i < 8;i++){ hidden[i] = new Percepton(); hidden[i].setInputNumber(input.length); } for(int i =0;i < 8;i++){ hidden2[i] = new Percepton(); hidden2[i].setInputNumber(input.length); } for(int i = 0;i < 3; i++){ output[i] = new Percepton(); output[i].setInputNumber(hidden.length); } } public void run(){ double[] temp = new double[10]; if(start){ StartTime = System.currentTimeMillis(); start = false; } CurrTime = System.currentTimeMillis(); if(CurrTime-StartTime > 5000){ ShooterLocationX=random.nextInt(400); ShooterLocationY=random.nextInt(275); shot.newX = ShooterLocationX+(shooterDiameter/2)-5; shot.newY = ShooterLocationY+(shooterDiameter/2)-5; shot.windSpeed = (float)(random.nextInt(200)-100)/100; start = true; if(!shotbeenFires){ error+=15; } for(int n = 0; n < output.length;n++){ output[n].learn(n, error, output[n].weights[n]); } for(int n = 0; n < hidden2.length;n++){ hidden2[n].learn(n, error, hidden2[n].weights[n]); } for(int n = 0; n < hidden.length;n++){ hidden[n].learn(n, error, hidden[n].weights[n]); } for(int n = 0; n < input.length;n++){ input[n].learn(n, error, input[n].weights[n]); } error = 0; shotbeenFires = false; } outputs1[0] = input[0].sigmoid((((Math.max(ShooterLocationX,targetX)-Math.min(ShooterLocationX,targetX))/300)*2)*input[0].weights[0],1*input[0].biasWeight); outputs1[1] = input[1].sigmoid((((Math.max(ShooterLocationY,targetY)-Math.min(ShooterLocationY,targetY))/150)*2)*input[1].weights[0],1*input[1].biasWeight); outputs1[2] = input[2].sigmoid((ShooterRotation)*input[2].weights[0],1*input[2].biasWeight); outputs1[3] = input[3].sigmoid((shot.windSpeed)*input[3].weights[0],1*input[3].biasWeight); System.out.println("\n"); for(int n = 0;n < hidden.length;n++){ for(int i = 0;i<temp.length;i++){ temp[i] = 0; } for(int i = 0;i < outputs1.length;i++){ temp[i] = outputs1[i]*hidden[n].weights[i]; } outputs2[n] = (float)DoubleStream.of(temp).sum(); outputs2[n] = hidden[1].sigmoid(outputs2[n],1*hidden[n].biasWeight); //System.out.print(outputs2[n]); } System.out.println("\n"); for(int n = 0;n < hidden2.length;n++){ for(int i = 0;i<temp.length;i++){ temp[i] = 0; } for(int i = 0;i < outputs2.length;i++){ temp[i] = outputs2[i]*hidden2[n].weights[i]; } outputs3[n] = (float)DoubleStream.of(temp).sum(); outputs3[n] = hidden2[1].sigmoid(outputs3[n],1*hidden2[n].biasWeight); //System.out.print(outputs3[n]); } System.out.println("\n"); for(int n = 0;n < output.length;n++){ for(int i = 0;i<temp.length;i++){ temp[i] = 0; } for(int i = 0;i < outputs1.length;i++){ temp[i] = outputs3[n]*hidden[n].weights[i]; } outputs4[n] = (float)DoubleStream.of(temp).sum(); outputs4[n] = output[n].sigmoid(outputs4[n],1*output[n].biasWeight); //System.out.print(outputs4[n]); } if(!ShotFired){ System.out.println("\n"); if(outputs4[0] > 0.5){ ShotFired = true; shot.rotation = ShooterRotation; } if (outputs4[1] > 0.5){ ShooterRotation = ShooterRotation + outputs3[1]; } if(outputs4[2] > 0.5){ ShooterRotation =ShooterRotation - outputs3[2]; } if(ShooterRotation*360 > 360){ ShooterRotation = ((ShooterRotation * 360) + 360) /360; }else if(ShooterRotation * 360 < 0){ ShooterRotation = ((ShooterRotation*360)-360) /360; } } for(int i = 0; i < 1; i++){ if(ShotFired){ shotbeenFires = true; shot.newLocationX(shot.newX); shot.newLocationY(shot.newY); } if(targetY < 20 ||targetY+targetLength >300){ direction = !direction; } if(direction){ targetY += 8; }else{ targetY -= 8; } if(shot.newX + (15)>= targetX && shot.newX + 15 < targetX +targetWidth && shot.newY + 15> targetY && shot.newY <targetY + targetLength){ System.out.println("Target Hit"); error -= 10; shot.newX = ShooterLocationX + shooterDiameter/2-5; shot.newY = ShooterLocationY + shooterDiameter/2-5; ShotFired = false; }else if(shot.newX > 600|| shot.newX<10||shot.newY<10||shot.newY> 290){ System.out.println("MISS"); error += (shot.newY - targetY); shot.newX = ShooterLocationX + shooterDiameter/2-5; shot.newY = ShooterLocationY + shooterDiameter/2-5; ShotFired = false; } } repaint(); } public void paint(Graphics g){ targetVectorX = ShooterLocationX + shooterDiameter/2 + Math.cos(Math.toRadians(ShooterRotation)) * 100; targetVectorY = ShooterLocationY + shooterDiameter/2 + Math.sin(Math.toRadians(ShooterRotation)) * 100; super.paint(g); Graphics2D g2 = (Graphics2D)g; g2.fillOval(ShooterLocationX, ShooterLocationY, shooterDiameter, shooterDiameter); g2.setPaint(Color.RED); g2.drawLine(ShooterLocationX + shooterDiameter/2, ShooterLocationY+shooterDiameter/2, (int)targetVectorX, (int)targetVectorY); g2.setPaint(Color.BLUE); g2.fillRect(targetX, targetY, targetWidth, targetLength); g2.setPaint(Color.RED); g2.fillOval((int)shot.newX, (int)shot.newY, 10, 10); g2.setPaint(Color.gray); g2.fillRect(600, 0, 300,300); for(int i = 0; i < input.length;i++){ if(outputs1[i] > 0.5){ g2.setPaint(; }else{ g2.setPaint(Color.white); } g2.drawOval(625+i*35, 250, 25, 25); for(int j = 0;j<hidden.length;j++){ g2.drawLine(640+i*35, 250, 615+j*30, 195); } } for(int i = 0; i < hidden.length;i++){ if(outputs2[i] > 0.5){ g2.setPaint(; }else{ g2.setPaint(Color.white); } g2.drawOval(605+i*30, 175, 20, 20); for(int j = 0;j<hidden2.length;j++){ g2.drawLine(615+i*30, 175, 615+j*30, 145); } } for(int i = 0; i < hidden2.length;i++){ if(outputs3[i] > 0.5){ g2.setPaint(; }else{ g2.setPaint(Color.white); } g2.drawOval(605+i*30, 125, 20, 20); for(int j = 0;j<output.length;j++){ g2.drawLine(615+i*30, 125, 697+j*50, 75); } } for(int i = 0; i < output.length;i++){ if(outputs4[i] > 0.5){ g2.setPaint(; }else{ g2.setPaint(Color.white); } g2.drawOval(685+i*50, 50, 25, 25); } try { Thread.sleep(100); } catch (InterruptedException e) { // TODO Auto-generated catch block e.printStackTrace(); } run(); } } public class Shooter { double windSpeed = 0.5; int distance = 0; double newX; double newY; double rotation; double temp = 0; public Shooter(double rotate){ rotation = rotate*360; windSpeed = windSpeed*5; } public void newLocationX(double XPrev){ newX = XPrev + Math.cos(Math.toRadians(rotation)) * 20; } public void newLocationY(double YPrev){ newY = YPrev + Math.sin(Math.toRadians(rotation)) * 20; newY =newY - windSpeed; } } import java.util.Random; public class Percepton { int numOfInputs = 100; float[] weights = new float[numOfInputs]; int sum; double learningRate = 0.1; float biasWeight; float a; float out; Random random = new Random(); public void setWeight(int index,float weight){ weights[index] = weight; } public void setInputNumber(int inputs){ numOfInputs = inputs; for(int i = 0; i < inputs; i++){ weights[i] = (float)(random.nextInt(400)-200)/200; biasWeight = (float)(random.nextInt(400)-200)/200; //System.out.println(weights[i]); } } public void learn(int index, double error, float value){ weights[index] += (float)learningRate * (float)error * value; } public double sigmoid(double input,double bias){ return (float) (1/(1+Math.exp(-input*bias))); } }

Category:java Views:2 Time:2016-11-29

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