private EvaluationInfo Test(IBlackBox phenome, int iterations)
{
Controller.NoveltySearch = NoveltySearchInfo;
Environment.NoveltySearch = NoveltySearchInfo;
Controller.Phenome = phenome;
// Deactivate novelty search for testing
bool novelty = NoveltySearchInfo.ScoreNovelty;
NoveltySearchInfo.ScoreNovelty = false;
EvaluationInfo evaluation = new EvaluationInfo();
evaluation.Iterations = iterations;
evaluation.ObjectiveFitnessIt = new double[iterations];
EvaluateRecord(Controller, iterations, ref evaluation);
CalculateTestStats(ref evaluation);
TearDownTest();
NoveltySearchInfo.ScoreNovelty = novelty;
Controller.Phenome = null;
return(evaluation);
}
/// <summary>
/// Main evaluation loop. Called from EA. Runs on separate / multiple threads.
/// </summary>
public EvaluationInfo Evaluate(IBlackBox phenome)
{
Environment.NoveltySearch = NoveltySearchInfo;
Controller.NoveltySearch = NoveltySearchInfo;
// Register the phenome
Controller.Phenome = phenome;
// Register controller to environment. Rarely used, since the environment usually does not need to know about the controller
Environment.Controller = Controller;
EvaluationInfo evaluation = new EvaluationInfo();
// Notify subclasses that the objective evaluation is about to start
OnObjectiveEvaluationStart();
// Evaluate objective!
EvaluateObjective(Controller, Iterations, ref evaluation);
if (NoveltySearchEnabled)
{
// Notify subclasses that the novelty evaluation is about to start
OnNoveltyEvaluationStart();
// Evaluate novelty!
EvaluateNovelty(Controller, ref evaluation);
}
// Unregister the phenome
Controller.Phenome = null;
// Increment evaluation count
_evaluationCount++;
// Check if the task has been solved
if (evaluation.ObjectiveFitness >= MaxScore * .999f)
{
_logger.Info($"Max fitness reached: {evaluation.ObjectiveFitness:F4}");
StopConditionSatisfied = true;
}
return(evaluation);
}
private void CalculateTestStats(ref EvaluationInfo info)
{
double total = 0;
double min = double.MaxValue;
double max = double.MinValue;
for (int i = 0; i < info.Iterations; i++)
{
double fitness = info.ObjectiveFitnessIt[i];
total += fitness;
if (fitness < min)
{
min = fitness;
}
if (fitness > max)
{
max = fitness;
}
}
double mean = total / info.Iterations;
double sdTotal = 0;
for (int i = 0; i < info.Iterations; i++)
{
double fitness = info.ObjectiveFitnessIt[i];
double v = fitness - mean;
sdTotal += v * v;
}
info.ObjectiveFitnessMean = mean;
info.ObjectiveFitnessStandardDeviation = Math.Sqrt(sdTotal / info.Iterations);
info.ObjectiveFitnessMax = max;
info.ObjectiveFitnessMin = min;
}
private static void GeneralizeAllChamps()
{
string[] xmls = Directory.EnumerateFiles(_currentDir, "champion*.xml").ToArray();
Console.WriteLine($"Found {xmls.Length} champion genomes");
int count = xmls.Length;
int iterations = GetIntegerConsoleInput("Enter number of iterations:");
NextExperiment();
EvaluationInfo[] results = new EvaluationInfo[count];
for (int i = 0; i < count; i++)
{
results[i] = _experiment.TestSavedChampion(xmls[i], iterations, 1, true, true)[0];
}
try
{
string genDataFile = $"{_currentDir}/{DATA_FILE_GEN}";
using (StreamWriter sw = File.AppendText(genDataFile))
{
sw.WriteLine("Genome", "Iterations", "Mean", "Standard Deviation", "Max", "Min");
for (int i = 0; i < count; i++)
{
EvaluationInfo res = results[i];
sw.WriteLine(string.Format(CultureInfo.InvariantCulture,
"{0},{1},{2:F4},{3:F4},{4:F4},{5:F4}",
res.GenomeId, res.Iterations, res.ObjectiveFitnessMean, res.ObjectiveFitnessStandardDeviation, res.ObjectiveFitnessMax, res.ObjectiveFitnessMin));
}
}
}
catch (Exception ex)
{
_logger.Warn($"Could not write to generalization file: {ex.Message}", ex);
}
Console.WriteLine("Done. Press any key to exit...");
Console.ReadKey();
}
private EvaluationInfo[] TestGenome(NeatGenome genome, int iterations, int runs, bool createRecordings, bool generalize)
{
if (runs <= 0)
{
return(new EvaluationInfo[0]);
}
if (_ea != null && _ea.RunState == RunState.Running)
{
_ea.RequestPause();
}
// Create the genome decoder
IGenomeDecoder <NeatGenome, IBlackBox> decoder = CreateGenomeDecoder();
// Decode the genome (genotype => phenotype)
IBlackBox phenome = decoder.Decode(genome);
//TODO FIXME We had problems with the logger, it hangs at some point probably a buffer issue on the windows cmd???
//We had to disable the console appender on log4net and just log to the file, so there is now a console writeline instead
Debug.On = true;
_logger.Info($"Testing phenome {(generalize ? "generalization " : "")}(ID: {genome.Id})...");
Console.WriteLine($"Testing phenome (ID: {genome.Id})...");
EvaluationInfo[] fitness = new EvaluationInfo[runs];
CreateExperimentDirectoryIfNecessary();
// run evaluations
double minFitness = double.MaxValue;
double maxFitness = double.MinValue;
for (int i = 0; i < runs; i++)
{
if (generalize)
{
fitness[i] = _evaluator.TestPhenomeGeneralization(phenome, iterations);
fitness[i].GenomeId = genome.Id;
}
else
{
fitness[i] = _evaluator.TestPhenome(phenome, iterations);
}
if (fitness[i].ObjectiveFitnessMean < minFitness)
{
minFitness = fitness[i].ObjectiveFitnessMean;
}
if (fitness[i].ObjectiveFitnessMean > maxFitness)
{
maxFitness = fitness[i].ObjectiveFitnessMean;
}
if (createRecordings)
{
if (Recorder != null)
{
string recordingFile = generalize
? $"{RecordingGeneralizationFile($"{genome.Id}_{i}")}"
: $"{RecordingFile($"{genome.Id}_{i}")}";
string tapeFile = generalize
? $"{TapeGeneralizationFile($"{genome.Id}_{i}")}"
: $"{TapeFile($"{genome.Id}_{i}")}";
using (Bitmap bmp = Recorder.LifetimeToBitmap())
{
bmp.Save(recordingFile, ImageFormat.Png);
}
if (Recorder.FinalTuringTape != null)
{
using (Bitmap bmp = Recorder.TapeToBitmap())
{
bmp.Save(tapeFile, ImageFormat.Png);
}
}
}
else
{
_logger.Warn("Recorder was null");
break;
}
_logger.Info($"Run {i}: Achieved fitness: {fitness[i].ObjectiveFitnessMean:F4}");
Console.WriteLine($"Run {i}: Achieved fitness: {fitness[i].ObjectiveFitnessMean:F4}");
}
}
// evaluate runs
if (runs > 1)
{
double[] fit = new double[runs];
for (int i = 0; i < runs; i++)
{
fit[i] = fitness[i].ObjectiveFitnessMean;
}
double mean = Utilities.Mean(fit);
double sd = Utilities.StandartDeviation(fit);
//TODO FIXME We had problems with the logger, it hangs at some point probably a buffer issue on the windows cmd???
//We had to disable the console appender on log4net and just log to the file, so there is now a console writeline instead
_logger.Info($"Done. Average fitness: {mean:F4}, min fitness: {minFitness:F4}, max fitness: {maxFitness:F4}, sd: {sd:F4}");
Console.WriteLine($"Done. Average fitness: {mean:F4}, min fitness: {minFitness:F4}, max fitness: {maxFitness:F4}, sd: {sd:F4}");
}
return(fitness);
}
protected abstract void EvaluateRecord(TController controller, int iterations, ref EvaluationInfo evaluation);
protected abstract void EvaluateNovelty(TController controller, ref EvaluationInfo evaluation);
protected abstract void EvaluateObjective(TController controller, int iterations, ref EvaluationInfo evaluation);
