// Update is called once per frame
void Update()
{
if (!weightsSet)
{
myNeuralNetwork.SetWeights(myAgent.myC.genes);
weightsSet = true;
}
if (transform.position.x <= -15)
{
transform.position = new Vector3(-15, transform.position.y, 0);
}
if (transform.position.x >= 15)
{
transform.position = new Vector3(15, transform.position.y, 0);
}
if (transform.position.y >= 10)
{
transform.position = new Vector3(transform.position.x, 10, 0);
}
if (transform.position.y <= -2.5f)
{
transform.position = new Vector3(transform.position.x, -2.5f, 0);
}
distance = Vector3.Distance(transform.position, target.transform.position);
if (reached)
{
myRB.Sleep();
if (transform.position.y < target.transform.position.y)
{
myAgent.SetFitness(20 - distance);
}
else
{
myAgent.SetFitness(20 - distance);
}
}
else
{
if (myAgent != null)
{
//if(actionCounter < actionTime) {
// actionCounter += Time.deltaTime;
// PerformAction();
//}else if(index >= 0) {
// index++;
// if (index < geneCount) {
// actionTime = myAgent.myC.genes[index].time;
// myAction = myAgent.myC.genes[index].action;
// currentThrust = myAgent.myC.genes[index].thrust;
// currentRot = myAgent.myC.genes[index].rotAmount;
// actionCounter = 0;
// }
//}else
// index++;
float angle = transform.eulerAngles.z % 360f;
if (angle < 0f)
{
angle += 360f;
}
Vector2 deltaVector = (target.transform.position - transform.position).normalized;
float rad = Mathf.Atan2(deltaVector.y, deltaVector.x);
rad *= Mathf.Rad2Deg;
rad = rad % 360;
if (rad < 0)
{
rad = 360 + rad;
}
rad = 90f - rad;
if (rad < 0f)
{
rad += 360f;
}
rad = 360 - rad;
rad -= angle;
if (rad < 0)
{
rad = 360 + rad;
}
if (rad >= 180f)
{
rad = 360 - rad;
rad *= -1f;
}
rad *= Mathf.Deg2Rad;
//if (actionCounter > actionTime) {
actionCounter = 0;
inputs[0] = rad / (Mathf.PI);
float[] output = myNeuralNetwork.ProcessInputs(inputs);
myRB.velocity = 2.5f * transform.up;
myRB.angularVelocity = 250 * output[0];
if (myRB.angularVelocity > 500)
{
myRB.angularVelocity = 500;
}
else if (myRB.angularVelocity < -500)
{
myRB.angularVelocity = -500;
}
if (output[0] == lastOutput[0])
{
constant = true;
}
else
{
constant = false;
}
lastOutput = output;
if (!constant)
{
myAgent.SetFitness(20 - distance);
}
else
{
myAgent.SetFitness(20 - distance);
}
//}else
// actionCounter += Time.deltaTime;
}
}
myAgent.myC.SetWeights(myNeuralNetwork.GetWeights());
}
