/// <summary>
/// Evaluate the provided phenome and return its fitness score.
/// This takes a blackbox (pretty much the decoded neuralnetwork (the phenome)) that input can be passed to
/// and output processed in the domain. Makes it very easy, we dont have to wory about the genome (genelist) or phenome (network) at all
/// </summary>
public FitnessInfo Evaluate(IBlackBox box)
{
// Set a maximum number of evaluations
_evalCount++;
double fitness = 0;
FitnessInfo fitnessInfo = new FitnessInfo(fitness, fitness);
if (_evalCount > _nextEvalStop)
{
_nextEvalStop += _evalBlockSize;
Debug.Log("Eval Count = " + _evalCount);
if (_evalCount >= 500000)
{
_stopConditionSatisfied = true;
}
}
// Only use player model if it has been initialized. Otherwise, all fitness is 0.5
if (_experiment.geomNodeList != null)
{
// Get highlevel features
PCGSharpHighLevelFeatures featureCounts = new PCGSharpHighLevelFeatures();
PCGSharpHighLevelFeatures.C_HL_ROOMTYPE lastRoomType = PCGSharpHighLevelFeatures.C_HL_ROOMTYPE.NoPreviousRoom;
if (_experiment == null)
{
Debug.Log("Experiment null");
}
if (_experiment.geomNodeList == null)
{
Debug.Log("Geom node list null");
}
for (int i = 0; i < _experiment.geomNodeList.Count; i++)
{
// Get cppn output for each node
box.InputSignalArray[0] = _experiment.geomNodeList[i].normDepth;
box.InputSignalArray[1] = _experiment.geomNodeList[i].normSiblingIndex;
box.ResetState();
box.Activate();
double[] outputs = new double[box.OutputCount];
for (int j = 0; j < box.OutputCount; j++)
{
outputs[j] = box.OutputSignalArray[j];
}
// Convert each nodes cppn output into a contentId
int combinedContentID = featureCounts.CPPNOutputToSettingsId(outputs);
lastRoomType = featureCounts.UpdateFeatures(combinedContentID, lastRoomType);
}
// Compare to the features of existing map
double difference = featureCounts.CompareToOther(_originalFeatures);
if (difference == 0)
{
_stopConditionSatisfied = true;
}
difference = 1000 + difference;
// Fitness is the membership to the "Like" class (positive class)
fitnessInfo = new FitnessInfo(difference, difference);
}
else
{
_stopConditionSatisfied = true;
}
return(fitnessInfo);
}
