public override void _Ready()
{
Node n = this;
Node rootNode = GetNode("/root");
while (agent == null && n != rootNode)
{
Node parent = n.GetParent();
n = parent;
agent = parent as RLAgent;
}
if (resettable)
{
agent.AddResetListener(this);
}
if (usePathAsID)
{
this.id = GetPath();
}
else
{
this.id = Name;
}
OnCreate();
}
public void Start()
{
if (target == null)
{
Debug.LogWarning("ForwardTargetReward error: target don't specified!");
}
agent = GetComponent <RLAgent>();
agent.AddResetListener(this);
minDist = -1;
}
void Start()
{
if (ignoreX)
{
fx = 0;
}
else
{
fx = 1;
}
if (ignoreY)
{
fy = 0;
}
else
{
fy = 1;
}
if (ignoreZ)
{
fz = 0;
}
else
{
fz = 1;
}
f = new Vector3(fx, fy, fz);
hist = new float[samples];
head = 0;
len = 0;
totalReceivedReward = 0.0f;
agent = GetComponent <RLAgent>();
agent.AddResetListener(this);
prevPosition = transform.localPosition;
if (samples <= 0)
{
Debug.LogWarning("Warning: the field samples value must be greater than 0!!!");
}
if (target == null)
{
Debug.LogWarning("Warning: target is not specified for reward function named AutoApproximationReward.");
}
}
// Start is called before the first frame update
void Start()
{
if (ignoreX)
{
fx = 0;
}
else
{
fx = 1;
}
if (ignoreY)
{
fy = 0;
}
else
{
fy = 1;
}
if (ignoreZ)
{
fz = 0;
}
else
{
fz = 1;
}
f = new Vector3(fx, fy, fz);
prevPosition = transform.localPosition;
agent = GetComponent <RLAgent>();
agent.AddResetListener(this);
sumOfRewards = 0;
}
void Start()
{
fall = false;
agent = GetComponent <RLAgent>();
agent.AddResetListener(this);
}