public void trainingStep(int ability, ref int pass)
{
pass++;
// 1. initiating ability
state = stAbilityExecuting;
// storing chosen ability
LastUsedAbility = ability;
// storing current input vectors
LastInputVecs = Robosapien.makeInputVector();
// finding the input vector for the top node
TopNodeInput = new double[Robosapien.CogTop.InputNum];
int i;
for (i = 0; i < Robosapien.CogTop.InputNum; i++)
{
TopNodeInput[i] = MetaNode.getOutput(Robosapien.CogTop.Children[i], LastInputVecs, pass);
}
// now training
double[] DesiredOutputVec = STANN.mapInt2VectorDouble(ability, 2, Robosapien.CogTop.stann.OutputNum);
// training 6 times
for (i = 0; i < 6; i++)
{
Robosapien.CogTop.stann.backPropagate(TopNodeInput, DesiredOutputVec);
}
// executing ability now..
Robosapien.useAbility((t_RSV2Ability)ability);
}
public void transitionAction(ref System.Windows.Forms.Panel panel,
System.Windows.Forms.TextBox[] texts, ref int pass)
{
switch (state)
{
case stIdle: // nothing
break;
case stSensorDataTransmission:
if (Robosapien.flagSensorDataAcquired)
{
Robosapien.fillSensorTexts(texts);
state = stFrameTransmission;
Robosapien.retrieveAbstraction();
}
break;
case stFrameTransmission:
if (Robosapien.flagAbstractionReady)
{
Robosapien.drawAbstraction(panel);
state = stAbilityExecuting;
// running the cognitive array now
double[][] inputVecs = Robosapien.makeInputVector();
pass++;
int output = (int)MetaNode.getOutput(Robosapien.CogTop, inputVecs, pass);
Robosapien.useAbility((t_RSV2Ability)output);
}
break;
case stAbilityExecuting:
if (Robosapien.flagAbilityDone)
{
Robosapien.flagAbilityDone = false;
state = stIdle;
}
break;
}
}
