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; } }