void findBestCar()
{
for (int i = 1; i < CarsList.Length; i++)
{
AICarSensors testCar = CarsList[i].GetComponent <AICarSensors>();
if (testCar.getBestCheckpoint() > bestCheckpoint)
{
bestAI.replaceValues(testCar.GetComponent <ValuesStorage>());
bestCheckpoint = testCar.getBestCheckpoint();
leastDistance = testCar.getDistanceToNextCheckpoint();
//print("Test car best checkpoint :" + testCar.getBestCheckpoint());
//print("Record holder best checkpoint :" + currentlyBestCar.getBestCheckpoint());
}
else if (testCar.getBestCheckpoint() == bestCheckpoint)
{
if (testCar.getDistanceToNextCheckpoint() < leastDistance)
{
bestAI.replaceValues(testCar.GetComponent <ValuesStorage>());
bestCheckpoint = testCar.getBestCheckpoint();
leastDistance = testCar.getDistanceToNextCheckpoint();
//print("Test car best checkpoint :" + testCar.getBestCheckpoint());
//print("Record holder best checkpoint :" + currentlyBestCar.getBestCheckpoint());
}
}
}
}
private void FixedUpdate()
{
startdelay -= Time.deltaTime;
if (startdelay < 0)
{
//reset the values in the nodes to 0 every frame
for (int i = 0; i < 8; i++)
{
layer2NodeValues[i] = 0;
if (i < 5)
{
triggerValues[i] = 0;
}
}
AICarSensors inputs = gameObject.GetComponent <AICarSensors>();
/// Check the first layer for nodes that fired, then perform additions if they did
for (int i = 0; i < 8; i++)
{
layer2NodeValues[i] += layer1Node1lines[i] * inputs.ForwardDist();
layer2NodeValues[i] += layer1Node2lines[i] * inputs.FrontLeftDist();
layer2NodeValues[i] += layer1Node3lines[i] * inputs.FrontRightDist();
layer2NodeValues[i] += layer1Node4lines[i] * inputs.FrontDownDist();
layer2NodeValues[i] += layer1Node5lines[i] * inputs.LeftDist();
layer2NodeValues[i] += layer1Node6lines[i] * inputs.RightDist();
layer2NodeValues[i] += layer1Node7lines[i] * inputs.BackLeftDist();
layer2NodeValues[i] += layer1Node8lines[i] * inputs.BackRightDist();
}
//apply a sigmoid function to the node values in order to lock them between 0 and 1
for (int i = 0; i < 8; i++)
{
layer2NodeValues[i] = sigmoid(layer2NodeValues[i]);
}
///End of the first layer firing its nodes
///Start second layer firing its nodes if they surpass the threshholds
for (int i = 0; i < 5; i++)
{
triggerValues[i] += layer2Node1lines[i] * layer2NodeValues[0];
triggerValues[i] += layer2Node2lines[i] * layer2NodeValues[1];
triggerValues[i] += layer2Node3lines[i] * layer2NodeValues[2];
triggerValues[i] += layer2Node4lines[i] * layer2NodeValues[3];
triggerValues[i] += layer2Node5lines[i] * layer2NodeValues[4];
triggerValues[i] += layer2Node6lines[i] * layer2NodeValues[5];
triggerValues[i] += layer2Node7lines[i] * layer2NodeValues[6];
triggerValues[i] += layer2Node8lines[i] * layer2NodeValues[7];
}
//apply a sigmoid function to the node values in order to lock them between 0 and 1
for (int i = 0; i < 5; i++)
{
triggerValues[i] = sigmoid(triggerValues[i]);
}
///End layer 2 nodes firing
///perform the action that the neural net tells the car to perform
AIDrivingActions controls = GetComponent <AIDrivingActions>();
float bestvalue = triggerValues[0];
int bestvaluenum = 0;
for (int i = 1; i < 5; i++)
{
if (triggerValues[i] > bestvalue)
{
bestvalue = triggerValues[i];
bestvaluenum = i;
}
}
switch (bestvaluenum)
{
case 0:
controls.TurnLeft();
break;
case 1:
controls.TurnRight();
break;
case 2:
controls.Accelerate();
break;
case 3:
controls.Decelerate();
break;
case 4:
controls.Jump();
break;
}
///End of the AI performing its Job
}
}
