/// <summary>
/// Performs multiple generations of the evolutionary algorithm.
/// </summary>
public void evolve(int generations)
{
for (int j = 0; j < generations; j++)
{
oneGeneration(j);
}
LogOutput.Close();
XmlDoc = new XmlDocument();
XmlGenomeWriterStatic.Write(XmlDoc, (NeatGenome)EA.BestGenome, ActivationFunctionFactory.GetActivationFunction("NullFn"));
OutputFileInfo = new FileInfo(Path.Combine(OutputFolder, "bestGenome.xml"));
XmlDoc.Save(OutputFileInfo.FullName);
//if doing novelty search, write out archive
if (experiment.DefaultNeatParameters.noveltySearch)
{
XmlDocument archiveout = new XmlDocument();
XmlPopulationWriter.WriteGenomeList(archiveout, EA.noveltyFixed.archive);
OutputFileInfo = new FileInfo(Path.Combine(OutputFolder, "archive.xml"));
archiveout.Save(OutputFileInfo.FullName);
}
// dump the MapElites grid contents (empty if we aren'type doing ME and we aren'type tracking ME-style-grid for some other algorithm)
XmlDocument gridout = new XmlDocument();
XmlPopulationWriter.WriteGenomeList(gridout, EA.meDumpGrid());
OutputFileInfo = new FileInfo(Path.Combine(OutputFolder, "finalgrid.xml"));
gridout.Save(OutputFileInfo.FullName);
}
private void EvolutionaryThread()
{
m_exp = CreateExperiment();
var idgen = new IdGenerator();
m_evoAlg = new EvolutionAlgorithm(
new Population(idgen,
GenomeFactory.CreateGenomeList(m_exp.DefaultNeatParameters, idgen,
m_exp.InputNeuronCount, m_exp.OutputNeuronCount,
m_exp.DefaultNeatParameters.pInitialPopulationInterconnections,
NeatExpParams.PopulationSize)),
m_exp.PopulationEvaluator, m_exp.DefaultNeatParameters);
while (!m_shouldQuit)
{
Console.WriteLine("::::: Performing one generation");
Console.WriteLine();
m_evoAlg.PerformOneGeneration();
if (NeatExpParams.SaveFitnessGrowth)
{
m_eaLogger.WriteLine(String.Format("{0,-10} {1,-20} {2,-20} {3,-20}",
m_evoAlg.Generation,
m_evoAlg.BestGenome.Fitness,
m_evoAlg.Population.MeanFitness, m_evoAlg.Population.AvgComplexity));
}
m_curBestGenome = m_evoAlg.BestGenome as NeatGenome;
if (m_evoAlg.BestGenome.Fitness > m_overalBestFitness)
{
m_overalBestFitness = m_evoAlg.BestGenome.Fitness;
m_overalBestGenome = m_curBestGenome;
if (NeatExpParams.SaveEachGenerationChampionCPPN)
{
try
{
var doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)m_evoAlg.BestGenome);
var oFileInfo = new FileInfo(Path.Combine(
NeatExpParams.EALogDir, String.Format("BestIndividual-{0}-{1}.xml", MyUnum, m_evoAlg.Generation.ToString())));
doc.Save(oFileInfo.FullName);
}
catch
{
}
}
}
if (EAUpdate != null)
{
EAUpdate.Invoke(this, EventArgs.Empty);
}
}
}
public void oneGeneration(int currentGeneration)
{
DateTime dt = DateTime.Now;
ea.PerformOneGeneration();
if (ea.BestGenome.RealFitness > maxFitness)
{
simExperiment.bestGenomeSoFar = (NeatGenome)ea.BestGenome;
maxFitness = ea.BestGenome.RealFitness;
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome);
oFileInfo = new FileInfo(outputFolder + "bestGenome" + currentGeneration.ToString() + ".xml");
doc.Save(oFileInfo.FullName);
}
//Console.WriteLine(ea.Generation.ToString() + " " + ea.BestGenome.RealFitness + " " + ea.Population.GenomeList.Count + " " + (DateTime.Now.Subtract(dt)));
// Schrum: Changed this to include fitness values from each environment: Mainly for FourTasks
Console.WriteLine(ea.Generation.ToString() + " " + ea.BestGenome.RealFitness + " " + ea.Population.GenomeList.Count + " (" + string.Join(",", ea.BestGenome.Behavior.objectives) + ") " + (DateTime.Now.Subtract(dt)) + " " + ea.BestGenome.Behavior.modules + " " + ea.BestGenome.Behavior.cppnLinks + " " + ea.BestGenome.Behavior.substrateLinks);
int gen_mult = 200;
if (logging)
{
if (experiment.DefaultNeatParameters.noveltySearch && currentGeneration % gen_mult == 0)
{
XmlDocument archiveout = new XmlDocument();
XmlPopulationWriter.WriteGenomeList(archiveout, ea.noveltyFixed.archive);
oFileInfo = new FileInfo(outputFolder + "archive.xml");
archiveout.Save(oFileInfo.FullName);
}
if ((experiment.DefaultNeatParameters.noveltySearch || experiment.DefaultNeatParameters.multiobjective) && currentGeneration % gen_mult == 0)
{
XmlDocument popout = new XmlDocument();
if (!experiment.DefaultNeatParameters.multiobjective)
{
XmlPopulationWriter.Write(popout, ea.Population, ActivationFunctionFactory.GetActivationFunction("NullFn"));
}
else
{
XmlPopulationWriter.WriteGenomeList(popout, ea.multiobjective.population);
}
oFileInfo = new FileInfo(outputFolder + "population" + currentGeneration.ToString() + ".xml");
popout.Save(oFileInfo.FullName);
}
// Schrum: Added contents of objective array to log so individual environment scores can be seen in FourTasks domain
// Also always print modules, cppn links, and substrate links
logOutput.WriteLine(ea.Generation.ToString() + " " + (maxFitness).ToString() + " " + string.Join(" ", ea.BestGenome.Behavior.objectives) + " " + ea.BestGenome.Behavior.modules + " " + ea.BestGenome.Behavior.cppnLinks + " " + ea.BestGenome.Behavior.substrateLinks);
}
}
public void addPending(bool suppressThresholdUpdate = false)
{
int length = pending_addition.Count;
if (!suppressThresholdUpdate)
{
if (length == 0)
{
archive_threshold *= 0.95;
}
if (length > 5)
{
archive_threshold *= 1.3;
}
}
for (int i = 0; i < length; i++)
{
if (measureAgainstArchive((NeatGenome.NeatGenome)pending_addition[i], false))
{
archive.Add(pending_addition[i]);
using (System.IO.StreamWriter file = new System.IO.StreamWriter("NoveltyLog.txt", true))
file.WriteLine(pending_addition[i].Fitness);
using (System.IO.StreamWriter file = new System.IO.StreamWriter(Chromaria.Modes.NoveltySearchRun.noveltyLogsFolder + "archive.txt", true))
{
// Write the genome's info to the novelty log
file.WriteLine("ID: " + pending_addition[i].GenomeId);
file.WriteLine("Fitness: " + pending_addition[i].Fitness);
file.Write("Behavior: ");
foreach (double behavior in pending_addition[i].Behavior.behaviorList)
{
file.Write(behavior.ToString() + ", ");
}
file.WriteLine();
file.WriteLine();
}
// Also print out the genome itself
XmlDocument doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome.NeatGenome)pending_addition[i]);
FileInfo oFileInfo = new FileInfo(Chromaria.Modes.NoveltySearchRun.noveltyLogsFolder + "genome" + pending_addition[i].GenomeId + ".xml");
doc.Save(oFileInfo.FullName);
}
}
pending_addition.Clear();
}
public void oneGeneration(int currentGeneration)
{
DateTime dt = DateTime.Now;
ea.PerformOneGeneration();
if (ea.BestGenome.RealFitness > maxFitness)
{
//simExperiment.bestGenomeSoFar = (NeatGenome)ea.BestGenome;
maxFitness = ea.BestGenome.RealFitness;
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome);
oFileInfo = new FileInfo(outputFolder + "bestGenome" + currentGeneration.ToString() + ".xml");
doc.Save(oFileInfo.FullName);
}
Console.WriteLine(ea.Generation.ToString() + " " + ea.BestGenome.RealFitness + " " + ea.Population.GenomeList.Count + " " + (DateTime.Now.Subtract(dt)));
int gen_mult = 200;
if (logging)
{
if (neatParams.noveltySearch && currentGeneration % gen_mult == 0)
{
XmlDocument archiveout = new XmlDocument();
XmlPopulationWriter.WriteGenomeList(archiveout, ea.noveltyFixed.archive);
oFileInfo = new FileInfo(outputFolder + "archive.xml");
archiveout.Save(oFileInfo.FullName);
}
if ((neatParams.noveltySearch || neatParams.multiobjective) && currentGeneration % gen_mult == 0)
{
XmlDocument popout = new XmlDocument();
if (!neatParams.multiobjective)
{
XmlPopulationWriter.Write(popout, ea.Population, ActivationFunctionFactory.GetActivationFunction("NullFn"));
}
else
{
XmlPopulationWriter.WriteGenomeList(popout, ea.multiobjective.population);
}
oFileInfo = new FileInfo(outputFolder + "population" + currentGeneration.ToString() + ".xml");
popout.Save(oFileInfo.FullName);
}
logOutput.WriteLine(ea.Generation.ToString() + " " + (maxFitness).ToString());
}
}
//private static Random random;
public static void Main(string[] args)
{
Util.Initialize(args[0]);
var idgen = new IdGenerator();
IExperiment experiment = new LimitExperiment();
XmlSerializer ser = new XmlSerializer(typeof(Settings));
//Settings settings = new Settings()
//{
// SmallBlind = 1,
// BigBlind = 2,
// GamesPerIndividual = 100,
// LogFile = "mutlithreaded_log.txt",
// MaxHandsPerTourney = 200,
// PlayersPerGame = 6,
// StackSize = 124,
// Threads = 4
//};
//ser.Serialize(new StreamWriter("settings.xml"), settings);
Settings settings = (Settings)ser.Deserialize(new StreamReader("settings.xml"));
var eval = new PokerPopulationEvaluator <SimpleLimitNeuralNetPlayer2, RingGamePlayerEvaluator>(settings);
var ea = new EvolutionAlgorithm(
new Population(idgen,
GenomeFactory.CreateGenomeList(experiment.DefaultNeatParameters,
idgen, experiment.InputNeuronCount,
experiment.OutputNeuronCount,
experiment.DefaultNeatParameters.pInitialPopulationInterconnections,
experiment.DefaultNeatParameters.populationSize)),
eval,
experiment.DefaultNeatParameters);
Console.WriteLine("Starting real evolution");
for (int i = 0; true; i++)
{
Console.WriteLine("Generation {0}", i + 1);
ea.PerformOneGeneration();
Console.WriteLine("Champion Fitness={0}", ea.BestGenome.Fitness);
var doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome);
FileInfo oFileInfo = new FileInfo("genomes_simple\\" + "bestGenome" + i.ToString() + ".xml");
doc.Save(oFileInfo.FullName);
}
}
public void saveGenome(IGenome genomeToSave)
{
try{
string genomeAttempt = genomeFileName(genomeToSave);
string genomePath = ExperimentDirectory + "/" + genomeAttempt;
if (!File.Exists(genomePath))
{
XmlDocument doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome.NeatGenome)genomeToSave);
doc.Save(genomePath);
}
}
catch (Exception e)
{
Console.WriteLine("Failed to write genome file: " + e.Message + " Genome: " + genomeToSave.GenomeId);
}
}
public void evolve(int generations)
{
for (int j = 0; j < generations; j++)
{
oneGeneration(j);
}
logOutput.Close();
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome, ActivationFunctionFactory.GetActivationFunction("NullFn"));
oFileInfo = new FileInfo(outputFolder + "bestGenome.xml");
doc.Save(oFileInfo.FullName);
//if doing novelty search, write out archive
if (neatParams.noveltySearch)
{
XmlDocument archiveout = new XmlDocument();
XmlPopulationWriter.WriteGenomeList(archiveout, ea.noveltyFixed.archive);
oFileInfo = new FileInfo(outputFolder + "archive.xml");
archiveout.Save(oFileInfo.FullName);
}
}
//Todo REFINE... adding highest fitness might
//not correspond with most novel?
public void add_most_novel(Population p)
{
double max_novelty = 0;
IGenome best = null;
for (int i = 0; i < p.GenomeList.Count; i++)
{
if (p.GenomeList[i].Fitness > max_novelty)
{
best = p.GenomeList[i];
max_novelty = p.GenomeList[i].Fitness;
}
}
archive.Add(best);
using (System.IO.StreamWriter file = new System.IO.StreamWriter(Chromaria.Modes.NoveltySearchRun.noveltyLogsFolder + "archive.txt", true))
{
// Write the genome's info to the novelty log
file.WriteLine("*BEST*");
file.WriteLine("ID: " + best.GenomeId);
file.WriteLine("Fitness: " + best.Fitness);
file.Write("Behavior: ");
foreach (double behavior in best.Behavior.behaviorList)
{
file.Write(behavior.ToString() + ", ");
}
file.WriteLine();
file.WriteLine();
}
// Also print out the genome itself
XmlDocument doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome.NeatGenome)best);
FileInfo oFileInfo = new FileInfo(Chromaria.Modes.NoveltySearchRun.noveltyLogsFolder + "genome" + best.GenomeId + ".xml");
doc.Save(oFileInfo.FullName);
}
/// <summary>
/// Runs one generation of the evolutionary algorithm.
/// </summary>
public void oneGeneration(int currentGeneration)
{
DateTime dt = DateTime.Now;
EA.PerformOneGeneration();
if (EA.BestGenome.RealFitness > MaxFitness)
{
SimExperiment.bestGenomeSoFar = (NeatGenome)EA.BestGenome;
MaxFitness = EA.BestGenome.RealFitness;
XmlDoc = new XmlDocument();
XmlGenomeWriterStatic.Write(XmlDoc, (NeatGenome)EA.BestGenome);
OutputFileInfo = new FileInfo(Path.Combine(OutputFolder, "bestGenome" + currentGeneration.ToString() + "_" + ((int)MaxFitness).ToString() + ".xml"));
XmlDoc.Save(OutputFileInfo.FullName);
}
if (experiment.DefaultNeatParameters.NS2 || experiment.DefaultNeatParameters.NSLC)
{
// The only reason NS2 has special output is so we can profile the novelty calc time versus the fitness calc time
Console.Write(EA.Generation.ToString() + " " + EA.BestGenome.RealFitness);
if (experiment.DefaultNeatParameters.NS1)
{
Console.Write(" nov: " + EA.ns1archiveAverageNovelty + " " + EA.Population.GenomeList.Count + "[" + EA.archiveSize + "]");
}
else
{
Console.Write(" nov: " + EA.averageNovelty + " " + EA.Population.GenomeList.Count + "[" + EA.archiveSize + "]");
}
if (experiment.DefaultNeatParameters.track_me_grid)
{
Console.Write("[" + EA.numFilledBins + "] " + EA.gridAverageFitness);
}
Console.WriteLine(" T-sim/nov/spe: " + EA.timeSpentInFitnessEval + " " + EA.timeSpentOutsideFitnessEval + " " + EA.timeSpentInSpeciation);
}
else if (experiment.DefaultNeatParameters.mapelites)
{
Console.WriteLine(EA.Generation.ToString() + " " + EA.BestGenome.RealFitness + " " + EA.Population.GenomeList.Count + "[" + EA.numFilledBins + "] " + EA.gridAverageFitness + " " + (DateTime.Now.Subtract(dt)));
}
else
{
Console.Write(EA.Generation.ToString() + " " + EA.BestGenome.RealFitness + " " + EA.Population.GenomeList.Count); // TODO: Add in average novelty
if (experiment.DefaultNeatParameters.track_me_grid)
{
Console.Write("[" + EA.numFilledBins + "] " + EA.gridAverageFitness);
}
Console.WriteLine(" " + (DateTime.Now.Subtract(dt)));
}
if (FinalPositionLogging)
{
foreach (IGenome g in EA.Population.GenomeList)
{
FinalPositionOutput.WriteLine(g.GenomeId + "," + g.Behavior.finalLocation[0] + "," + g.Behavior.finalLocation[1]);
}
}
if (TrajectoryLogging)
{
// If this is the first generation, create the new output folder
if (currentGeneration == 0)
{
TrajectoryFolderPath = Path.Combine(OutputFolder, "trajectories-" + FolderNum.ToString());
if (!Directory.Exists(TrajectoryFolderPath))
{
System.IO.Directory.CreateDirectory(TrajectoryFolderPath);
}
}
foreach (IGenome g in EA.Population.GenomeList)
{
// Check to see if we need to create a new folder
if (NumTrajectoriesRecorded == NumTrajectoriesPerFolder)
{
NumTrajectoriesRecorded = 0;
FolderNum++;
TrajectoryFolderPath = Path.Combine(OutputFolder, "trajectories-" + FolderNum.ToString());
if (!Directory.Exists(TrajectoryFolderPath))
{
System.IO.Directory.CreateDirectory(TrajectoryFolderPath);
}
}
// Print the Trajectory
using (System.IO.StreamWriter file = new System.IO.StreamWriter(Path.Combine(TrajectoryFolderPath, NumTrajectoriesRecorded.ToString() + ".txt"), true))
{
file.WriteLine("x,y");
foreach (double component in g.Behavior.trajectory)
{
file.Write(component.ToString() + ",");
}
}
// Increment the Trajectory counter
NumTrajectoriesRecorded++;
}
}
int gen_mult = 200;
if (Logging)
{
if (experiment.DefaultNeatParameters.noveltySearch && currentGeneration % gen_mult == 0)
{
XmlDocument archiveout = new XmlDocument();
XmlPopulationWriter.WriteGenomeList(archiveout, EA.noveltyFixed.archive);
OutputFileInfo = new FileInfo(Path.Combine(OutputFolder, "archive.xml"));
archiveout.Save(OutputFileInfo.FullName);
}
// If doing MapElites: print base500 generation instead of regular, and also print averageFitness and number of filled bins (instead of not)
// regular: generation bestfitness
// mapelites: generation500 bestfitness [numfilledgrids] averagefitness
if (experiment.DefaultNeatParameters.mapelites)
{
LogOutput.WriteLine(EA.generationBase500.ToString() + " " + (MaxFitness).ToString() + " " + EA.numFilledBins.ToString() + " " + EA.averageFitness.ToString());
LogOutput.Flush();
if (FinalPositionLogging)
{
foreach (IGenome g in EA.addedToArchive)
{
ArchiveModificationOutput.WriteLine(g.GenomeId + ",+," + EA.numEvaluations + "," + g.Behavior.finalLocation[0] + "," + g.Behavior.finalLocation[1]);
}
EA.addedToArchive.Clear();
foreach (IGenome g in EA.removedFromArchive)
{
ArchiveModificationOutput.WriteLine(g.GenomeId + ",-," + EA.numEvaluations + "," + g.Behavior.finalLocation[0] + "," + g.Behavior.finalLocation[1]);
}
EA.removedFromArchive.Clear();
}
}
else if (experiment.DefaultNeatParameters.NS2 || experiment.DefaultNeatParameters.NSLC)
{
LogOutput.Write(EA.generationBase500.ToString() + " " + (MaxFitness).ToString() + " " + EA.archiveSize + " " + EA.averageFitness.ToString() + " " + (EA.ns1 ? EA.ns1archiveAverageNovelty.ToString() : EA.averageNovelty.ToString()));
if (experiment.DefaultNeatParameters.track_me_grid)
{
LogOutput.Write(" " + EA.numFilledBins.ToString() + " " + EA.gridAverageFitness.ToString());
}
LogOutput.WriteLine();
LogOutput.Flush();
if (FinalPositionLogging)
{
foreach (IGenome g in EA.addedToArchive)
{
ArchiveModificationOutput.WriteLine(g.GenomeId + ",+," + EA.numEvaluations + "," + g.Behavior.finalLocation[0] + "," + g.Behavior.finalLocation[1]);
}
EA.addedToArchive.Clear();
foreach (IGenome g in EA.removedFromArchive)
{
ArchiveModificationOutput.WriteLine(g.GenomeId + ",-," + EA.numEvaluations + "," + g.Behavior.finalLocation[0] + "," + g.Behavior.finalLocation[1]);
}
EA.removedFromArchive.Clear();
}
}
else
{
LogOutput.Write(EA.generationBase500.ToString() + " " + (MaxFitness).ToString());
if (experiment.DefaultNeatParameters.track_me_grid)
{
LogOutput.Write(" " + EA.numFilledBins.ToString() + " " + EA.gridAverageFitness.ToString());
}
LogOutput.WriteLine();
LogOutput.Flush();
}
// Output complexity statistics
ComplexityOutput.WriteLine(EA.avgComplexity + ", " + EA.stdevComplexity + ", " + EA.minComplexity + ", " + EA.maxComplexity);
ComplexityOutput.Flush();
}
}
static void Main(string[] args)
{
NeatGenome seedGenome = null;
string filename = @"seedGenome.xml";
try
{
XmlDocument document = new XmlDocument();
document.Load(filename);
seedGenome = XmlNeatGenomeReaderStatic.Read(document);
}
catch (Exception e)
{
System.Console.WriteLine("Problem loading genome. \n" + e.Message);
}
string experimentName = "_2Pref";
for (int k = 3; k < 10; k++)
{
double maxFitness = 0;
int maxGenerations = 400; //150;
int populationSize = 300; //100;//150;
Thread extraWindowThread;
extraWindowThread = new System.Threading.Thread(delegate()
{
var myForm = new SharpNeatExperiments.Pacman.MyForm1();
System.Windows.Forms.Application.Run(myForm);
});
extraWindowThread.Start();
IExperiment exp = null;
//exp = new SUPGONLYExperiment(4,12,12,5,2);
//exp = new PacmanExperimentSUPG(4, 12, 12, 5, 2);
//exp = new SPMMExperiment(4, 12, 12, 5, 2);
//exp = new SPCExperiment(4, 12, 12, 5, 2);
exp = new SPSUPGExperiment(4, 12, 12, 5, 6);
StreamWriter SW;
SW = File.CreateText("logfile.txt");
//Change this line for different experiments
XmlDocument doc;
FileInfo oFileInfo;
IdGenerator idgen;
EvolutionAlgorithm ea;
if (seedGenome == null)
{
idgen = new IdGenerator();
ea = new EvolutionAlgorithm(new Population(idgen, GenomeFactory.CreateGenomeList(exp.DefaultNeatParameters, idgen, exp.InputNeuronCount, exp.OutputNeuronCount, exp.DefaultNeatParameters.pInitialPopulationInterconnections, populationSize)), exp.PopulationEvaluator, exp.DefaultNeatParameters);
}
else
{
idgen = new IdGeneratorFactory().CreateIdGenerator(seedGenome);
ea = new EvolutionAlgorithm(new Population(idgen, GenomeFactory.CreateGenomeList(seedGenome, exp.DefaultNeatParameters.populationSize, exp.DefaultNeatParameters, idgen)), exp.PopulationEvaluator, exp.DefaultNeatParameters);
}
bool isNSGAiiEnabled = false;
for (int j = 0; j < maxGenerations; j++)
{
DateTime dt = DateTime.Now;
if (isNSGAiiEnabled)
{
ea.PerformOneGenerationNSGAii();
}
else
{
ea.PerformOneGeneration();
}
if (ea.BestGenome.Fitness > maxFitness)
{
maxFitness = ea.BestGenome.Fitness;
Console.WriteLine(maxFitness + "maxFitness");
Console.WriteLine("objectiveFitness" + ea.BestGenome.MultiObjectiveFitness[0] + " " + ea.BestGenome.MultiObjectiveFitness[1]);
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome);
oFileInfo = new FileInfo("bestGenome" + j.ToString() + ".xml");
doc.Save(oFileInfo.FullName);
//MadsXMLWriter(j, maxFitness);
}
MadsXMLWriter(j, maxFitness, k, experimentName);
Console.WriteLine(ea.Generation.ToString() + " " + (maxFitness).ToString() + " " + (DateTime.Now.Subtract(dt)));
//Do any post-hoc stuff here
SW.WriteLine(ea.Generation.ToString() + " " + (maxFitness).ToString());
}
SW.Close();
//----- Write the genome to an XmlDocument.
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome, ActivationFunctionFactory.GetActivationFunction("NullFn"));
oFileInfo = new FileInfo("bestGenome" + experimentName + "_" + k + ".xml");
doc.Save(oFileInfo.FullName);
}
}
/// <summary>
/// This method is called when one individual finishes its run in the world (either because it planted itself
/// or because it timed out). It should ONLY be called when the creature is being controlled by a neural network (novelty search or evolution).
/// </summary>
///
private void ResetToFirstTrial()
{
// Reset numUpdates
numUpdates = 0;
// Remove the creature from the old region lists
// Update the region lists
foreach (List <int> region in regions)
{
region.RemoveAt(indexOfCurrentCreature);
}
// If the creature has already completed both trials, we need to _actually_ reset the simulator.
#region Planter XML writing
if (GenomeIndexOfCurrentCreature != -1)
{
// First, check to see if the individual was a valid planter
if (freezeAfterPlanting)
{
// Success on both trials
if (plantedInColoredSpace1 && plantedInColoredSpace2)
{
numBidirectionalPlanters++;
XmlDocument results = new XmlDocument();
XmlDeclaration declaration = results.CreateXmlDeclaration("1.0", null, null);
results.AppendChild(declaration);
XmlGenomeWriterStatic.Write(results, (NeatGenome)ea.Population.GenomeList[GenomeIndexOfCurrentCreature]);
results.Save(plantersFolder + "NoveltySearch_BidirectionalPlanterGenome" + numBidirectionalPlanters.ToString() + ".xml");
}
// Success on the first trial
else if (plantedInColoredSpace1)
{
numFirstTrialPlanters++;
XmlDocument results = new XmlDocument();
XmlDeclaration declaration = results.CreateXmlDeclaration("1.0", null, null);
results.AppendChild(declaration);
XmlGenomeWriterStatic.Write(results, (NeatGenome)ea.Population.GenomeList[GenomeIndexOfCurrentCreature]);
results.Save(plantersFolder + "NoveltySearch_FirstTrialPlanterGenome" + numFirstTrialPlanters.ToString() + ".xml");
}
// Sucess on the second trial
else if (plantedInColoredSpace2)
{
numSecondTrialPlanters++;
XmlDocument results = new XmlDocument();
XmlDeclaration declaration = results.CreateXmlDeclaration("1.0", null, null);
results.AppendChild(declaration);
XmlGenomeWriterStatic.Write(results, (NeatGenome)ea.Population.GenomeList[GenomeIndexOfCurrentCreature]);
results.Save(plantersFolder + "NoveltySearch_SecondTrialPlanterGenome" + numSecondTrialPlanters.ToString() + ".xml");
}
}
else
{
// Success on both trials, no misplanting
if (plantedInColoredSpace1 && plantedInColoredSpace2 && !plantedInWhiteSpace1 && !plantedInWhiteSpace2)
{
numBidirectionalPlanters++;
XmlDocument results = new XmlDocument();
XmlDeclaration declaration = results.CreateXmlDeclaration("1.0", null, null);
results.AppendChild(declaration);
XmlGenomeWriterStatic.Write(results, (NeatGenome)ea.Population.GenomeList[GenomeIndexOfCurrentCreature]);
results.Save(plantersFolder + "NoveltySearch_BidirectionalPlanterGenome" + numBidirectionalPlanters.ToString() + ".xml");
}
// Planted only in white
// Success on the first trial, no misplanting
else if (!plantedInColoredSpace1 && plantedInWhiteSpace1)
{
numFirstTrialPlanters++;
XmlDocument results = new XmlDocument();
XmlDeclaration declaration = results.CreateXmlDeclaration("1.0", null, null);
results.AppendChild(declaration);
XmlGenomeWriterStatic.Write(results, (NeatGenome)ea.Population.GenomeList[GenomeIndexOfCurrentCreature]);
results.Save(plantersFolder + "NoveltySearch_FirstTrialPlanterGenome_White" + numFirstTrialPlanters.ToString() + ".xml");
}
// Success on the first trial, no misplanting
else if (plantedInColoredSpace1 && !plantedInWhiteSpace1)
{
numFirstTrialPlanters++;
XmlDocument results = new XmlDocument();
XmlDeclaration declaration = results.CreateXmlDeclaration("1.0", null, null);
results.AppendChild(declaration);
XmlGenomeWriterStatic.Write(results, (NeatGenome)ea.Population.GenomeList[GenomeIndexOfCurrentCreature]);
results.Save(plantersFolder + "NoveltySearch_FirstTrialPlanterGenome" + numFirstTrialPlanters.ToString() + ".xml");
}
// Sucess on the second trial, no misplanting
else if (plantedInColoredSpace2 && !plantedInWhiteSpace2)
{
numSecondTrialPlanters++;
XmlDocument results = new XmlDocument();
XmlDeclaration declaration = results.CreateXmlDeclaration("1.0", null, null);
results.AppendChild(declaration);
XmlGenomeWriterStatic.Write(results, (NeatGenome)ea.Population.GenomeList[GenomeIndexOfCurrentCreature]);
results.Save(plantersFolder + "NoveltySearch_SecondTrialPlanterGenome" + numSecondTrialPlanters.ToString() + ".xml");
}
// Success on both trials, but with misplanting
if ((plantedInColoredSpace1 && plantedInWhiteSpace1) || (plantedInColoredSpace2 && plantedInWhiteSpace2))
{
numBidirectionalMisplanters++;
XmlDocument results = new XmlDocument();
XmlDeclaration declaration = results.CreateXmlDeclaration("1.0", null, null);
results.AppendChild(declaration);
XmlGenomeWriterStatic.Write(results, (NeatGenome)ea.Population.GenomeList[GenomeIndexOfCurrentCreature]);
results.Save(plantersFolder + "NoveltySearch_BidirectionalPlanterGenome_Misplanted" + numBidirectionalMisplanters.ToString() + ".xml");
}
// Success on the first trial, but with misplanting
else if (plantedInColoredSpace1 && plantedInWhiteSpace1)
{
numFirstTrialMisplanters++;
XmlDocument results = new XmlDocument();
XmlDeclaration declaration = results.CreateXmlDeclaration("1.0", null, null);
results.AppendChild(declaration);
XmlGenomeWriterStatic.Write(results, (NeatGenome)ea.Population.GenomeList[GenomeIndexOfCurrentCreature]);
results.Save(plantersFolder + "NoveltySearch_FirstTrialPlanterGenome_Misplanted" + numFirstTrialMisplanters.ToString() + ".xml");
}
// Sucess on the second trial, but with misplanting
else if (plantedInColoredSpace2 && plantedInWhiteSpace2)
{
numSecondTrialMisplanters++;
XmlDocument results = new XmlDocument();
XmlDeclaration declaration = results.CreateXmlDeclaration("1.0", null, null);
results.AppendChild(declaration);
XmlGenomeWriterStatic.Write(results, (NeatGenome)ea.Population.GenomeList[GenomeIndexOfCurrentCreature]);
results.Save(plantersFolder + "NoveltySearch_SecondTrialPlanterGenome_Misplanted" + numSecondTrialMisplanters.ToString() + ".xml");
}
}
}
#endregion
// Remove the individual from the global image list
Components.Remove(currentCreature);
// Reset the success flags
plantedInColoredSpace1 = false;
plantedInWhiteSpace1 = false;
plantedInColoredSpace2 = false;
plantedInWhiteSpace2 = false;
// Also reset the trial flag
firstTrial = true;
// Get the next creature for this generation, decode its CPPN, and replace the creature's controller
GenomeIndexOfCurrentCreature++;
// Update the folders for storing the archive and planters if necessary
if (GenomeIndexOfCurrentCreature % numCreaturesPerFolder == 0)
{
int newFolderNumber = GenomeIndexOfCurrentCreature / numCreaturesPerFolder;
noveltyLogsFolder = Directory.GetCurrentDirectory() + "\\archive\\" + newFolderNumber + "\\";
if (!Directory.Exists(noveltyLogsFolder))
{
Directory.CreateDirectory(noveltyLogsFolder);
}
plantersFolder = Directory.GetCurrentDirectory() + "\\planters\\" + newFolderNumber + "\\";
if (!Directory.Exists(plantersFolder))
{
Directory.CreateDirectory(plantersFolder);
}
}
// Initialize the genome's behavior characterization structure if this genome has not previously been evaluated
if (ea.Population.GenomeList[GenomeIndexOfCurrentCreature].Behavior == null)
{
ea.Population.GenomeList[GenomeIndexOfCurrentCreature].Behavior = new BehaviorType();
ea.Population.GenomeList[GenomeIndexOfCurrentCreature].Behavior.behaviorList = new List <double>();
}
INetwork newController = controllerSubstrate.generateGenome(ea.Population.GenomeList[GenomeIndexOfCurrentCreature].Decode(ActivationFunctionFactory.GetActivationFunction("BipolarSigmoid"))).Decode(ActivationFunctionFactory.GetActivationFunction("BipolarSigmoid"));
if (bidirectionalTrials)
{
currentCreature = new NNControlledCreature(morphology, initialBoardWidth / 2, initialBoardHeight / 2, initialHeading + (float)(Math.PI / 2.0), newController, this, drawSensorField, trackPlanting, defaultNumSensors, freezeAfterPlanting);
}
else
{
currentCreature = new NNControlledCreature(morphology, initialBoardWidth / 2, initialBoardHeight / 2, initialHeading, newController, this, drawSensorField, trackPlanting, defaultNumSensors, freezeAfterPlanting);
}
// Add the creature back into the appropriate region lists
RotationPacket rp = currentCreature.getRotationPacket();
regions[rp.NWCoord.Y / regionHeight, rp.NWCoord.X / regionWidth].Add(indexOfCurrentCreature);
if ((rp.NWCoord.X % regionWidth > rp.SECoord.X % regionWidth) && (rp.NWCoord.Y % regionHeight > rp.SECoord.Y % regionHeight))
{
regions[rp.SECoord.Y / regionHeight, rp.SECoord.X / regionWidth].Add(indexOfCurrentCreature);
}
if (rp.NWCoord.X % regionWidth > rp.SECoord.X % regionWidth)
{
regions[(rp.NWCoord.Y / regionHeight), rp.SECoord.X / regionWidth].Add(indexOfCurrentCreature);
}
if (rp.NWCoord.Y % regionHeight > rp.SECoord.Y % regionHeight)
{
regions[rp.SECoord.Y / regionHeight, rp.SECoord.X / regionWidth].Add(indexOfCurrentCreature);
}
}
private void startEvolutionToolStripMenuItem_Click(object sender, EventArgs e)
{
NeatGenome seedGenome = null;
if (EvoSeedFileName != null)
{
try
{
XmlDocument document = new XmlDocument();
document.Load(EvoSeedFileName);
seedGenome = XmlNeatGenomeReaderStatic.Read(document);
}
catch (Exception ex)
{
System.Console.WriteLine("Problem loading genome. \n" + ex.Message);
}
}
double maxFitness = 0;
int maxGenerations = 1000;
int populationSize = 150;
int inputs = 4;
IExperiment exp = new SkirmishExperiment(inputs, 1, EvoIsMulti, EvoShape);
w = SkirmishNetworkEvaluator.lWorldVar(network, 125);
timer = 0;
StreamWriter SW;
SW = File.CreateText(EvoOutputLogFolder + "logfile.txt");
XmlDocument doc;
FileInfo oFileInfo;
IdGenerator idgen;
EvolutionAlgorithm ea;
if (seedGenome == null)
{
idgen = new IdGenerator();
ea = new EvolutionAlgorithm(
new Population(idgen,
GenomeFactory.CreateGenomeList(
exp.DefaultNeatParameters, idgen,
exp.InputNeuronCount, exp.OutputNeuronCount,
exp.DefaultNeatParameters.pInitialPopulationInterconnections,
populationSize)),
exp.PopulationEvaluator, exp.DefaultNeatParameters);
}
else
{
idgen = new IdGeneratorFactory().CreateIdGenerator(seedGenome);
ea = new EvolutionAlgorithm(new Population(idgen, GenomeFactory.CreateGenomeList(seedGenome, populationSize, exp.DefaultNeatParameters, idgen)), exp.PopulationEvaluator, exp.DefaultNeatParameters);
}
for (int j = 0; j < maxGenerations; j++)
{
DateTime dt = DateTime.Now;
ea.PerformOneGeneration();
if (ea.BestGenome.Fitness > maxFitness)
{
maxFitness = ea.BestGenome.Fitness;
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome);
oFileInfo = new FileInfo(EvoOutputLogFolder + "bestGenome" + j.ToString() + ".xml");
doc.Save(oFileInfo.FullName);
// This will output the substrate, uncomment if you want that
/* doc = new XmlDocument();
* XmlGenomeWriterStatic.Write(doc, (NeatGenome) SkirmishNetworkEvaluator.substrate.generateMultiGenomeModulus(ea.BestGenome.Decode(null),5));
* oFileInfo = new FileInfo(folder + "bestNetwork" + j.ToString() + ".xml");
* doc.Save(oFileInfo.FullName);
*/
}
Console.WriteLine(ea.Generation.ToString() + " " + ea.BestGenome.Fitness + " " + (DateTime.Now.Subtract(dt)));
//Do any post-hoc stuff here
SW.WriteLine(ea.Generation.ToString() + " " + (maxFitness).ToString());
}
SW.Close();
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome, ActivationFunctionFactory.GetActivationFunction("NullFn"));
oFileInfo = new FileInfo(EvoOutputLogFolder + "bestGenome.xml");
doc.Save(oFileInfo.FullName);
}
static void Main(string[] args)
{
string folder = "";
NeatGenome seedGenome = null;
string filename = null;
string shape = "triangle";
bool isMulti = false;
for (int j = 0; j < args.Length; j++)
{
if (j <= args.Length - 2)
{
switch (args[j])
{
case "-seed": filename = args[++j];
Console.WriteLine("Attempting to use seed from file " + filename);
break;
case "-folder": folder = args[++j];
Console.WriteLine("Attempting to output to folder " + folder);
break;
case "-shape": shape = args[++j];
Console.WriteLine("Attempting to do experiment with shape " + shape);
break;
case "-multi": isMulti = Boolean.Parse(args[++j]);
Console.WriteLine("Experiment is heterogeneous? " + isMulti);
break;
}
}
}
if (filename != null)
{
try
{
XmlDocument document = new XmlDocument();
document.Load(filename);
seedGenome = XmlNeatGenomeReaderStatic.Read(document);
}
catch (Exception e)
{
System.Console.WriteLine("Problem loading genome. \n" + e.Message);
}
}
double maxFitness = 0;
int maxGenerations = 1000;
int populationSize = 150;
int inputs = 4;
IExperiment exp = new SkirmishExperiment(inputs, 1, isMulti, shape);
StreamWriter SW;
SW = File.CreateText(folder + "logfile.txt");
XmlDocument doc;
FileInfo oFileInfo;
IdGenerator idgen;
EvolutionAlgorithm ea;
if (seedGenome == null)
{
idgen = new IdGenerator();
ea = new EvolutionAlgorithm(new Population(idgen, GenomeFactory.CreateGenomeList(exp.DefaultNeatParameters, idgen, exp.InputNeuronCount, exp.OutputNeuronCount, exp.DefaultNeatParameters.pInitialPopulationInterconnections, populationSize)), exp.PopulationEvaluator, exp.DefaultNeatParameters);
}
else
{
idgen = new IdGeneratorFactory().CreateIdGenerator(seedGenome);
ea = new EvolutionAlgorithm(new Population(idgen, GenomeFactory.CreateGenomeList(seedGenome, populationSize, exp.DefaultNeatParameters, idgen)), exp.PopulationEvaluator, exp.DefaultNeatParameters);
}
for (int j = 0; j < maxGenerations; j++)
{
DateTime dt = DateTime.Now;
ea.PerformOneGeneration();
if (ea.BestGenome.Fitness > maxFitness)
{
maxFitness = ea.BestGenome.Fitness;
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome);
oFileInfo = new FileInfo(folder + "bestGenome" + j.ToString() + ".xml");
doc.Save(oFileInfo.FullName);
// This will output the substrate, uncomment if you want that
/* doc = new XmlDocument();
* XmlGenomeWriterStatic.Write(doc, (NeatGenome) SkirmishNetworkEvaluator.substrate.generateMultiGenomeModulus(ea.BestGenome.Decode(null),5));
* oFileInfo = new FileInfo(folder + "bestNetwork" + j.ToString() + ".xml");
* doc.Save(oFileInfo.FullName);
*/
}
Console.WriteLine(ea.Generation.ToString() + " " + ea.BestGenome.Fitness + " " + (DateTime.Now.Subtract(dt)));
//Do any post-hoc stuff here
SW.WriteLine(ea.Generation.ToString() + " " + (maxFitness).ToString());
}
SW.Close();
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome, ActivationFunctionFactory.GetActivationFunction("NullFn"));
oFileInfo = new FileInfo(folder + "bestGenome.xml");
doc.Save(oFileInfo.FullName);
}
public void run(int type, int evaluationMethod, System.Threading.CancellationToken token)
{
double maxFitness = 0;
int maxGenerations = 800;
int populationSize = 300;
IExperiment exp;
if (evaluationMethod == 1)
{
novelty = true;
}
if (type == 0)
{
exp = new CTRNNExperiment(4, 12, 8, 8, 4);
}
else if (type == 1)
{
exp = new SUPGExperiment(4, 12, 12, 3, 2);
}
else
{
doClune = true;
exp = new CluneExperiment(20, 20, 20, 6, 1);
}
XmlDocument doc;
FileInfo oFileInfo;
IdGenerator idgen;
EvolutionAlgorithm ea;
NeatGenome seedGenome = null;
if (seedGenome == null)
{
idgen = new IdGenerator();
ea = new EvolutionAlgorithm(new Population(idgen, GenomeFactory.CreateGenomeList(exp.DefaultNeatParameters, idgen, exp.InputNeuronCount, exp.OutputNeuronCount, exp.DefaultNeatParameters.pInitialPopulationInterconnections, populationSize)), exp.PopulationEvaluator, exp.DefaultNeatParameters);
}
else
{
idgen = new IdGeneratorFactory().CreateIdGenerator(seedGenome);
ea = new EvolutionAlgorithm(new Population(idgen, GenomeFactory.CreateGenomeList(seedGenome, populationSize, exp.DefaultNeatParameters, idgen)), exp.PopulationEvaluator, exp.DefaultNeatParameters);
}
Directory.CreateDirectory(folder);
using (var logWriter = File.CreateText(folder + "Log " + DateTime.Now.ToString("u").Replace(':', '.') + ".txt"))
for (int j = 0; j < maxGenerations; j++)
{
if (token.IsCancellationRequested)
{
logWriter.WriteLine("Cancelled");
break;
}
DateTime dt = DateTime.Now;
ea.PerformOneGeneration();
if (ea.BestGenome.ObjectiveFitness > maxFitness)
{
maxFitness = ea.BestGenome.ObjectiveFitness;
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome);
oFileInfo = new FileInfo(folder + "bestGenome" + j + ".xml");
doc.Save(oFileInfo.FullName);
/*/ This will output the substrate
* doc = new XmlDocument();
* XmlGenomeWriterStatic.Write(doc, SUPGNetworkEvaluator.substrate.generateGenome(ea.BestGenome.Decode(null)));
* oFileInfo = new FileInfo(folder + "bestNetwork" + j + ".xml");
* doc.Save(oFileInfo.FullName);*/
}
var msg = DateTime.Now.ToLongTimeString()
+ "; Duration=" + DateTime.Now.Subtract(dt).ToString("mm\\:ss")
+ "; Gen=" + ea.Generation.ToString("000") + "; Neurons=" + (ea.Population.TotalNeuronCount / (float)ea.Population.GenomeList.Count).ToString("00.00") + "; Connections=" + (ea.Population.TotalConnectionCount / (float)ea.Population.GenomeList.Count).ToString("00.00")
+ "; BestFit=" + ea.BestGenome.ObjectiveFitness.ToString("0.000") + "; MaxFit=" + maxFitness.ToString("0.000");
Console.WriteLine(msg);
logWriter.WriteLine(msg);
logWriter.Flush();
//Do any post-hoc stuff here
}
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome, ActivationFunctionFactory.GetActivationFunction("NullFn"));
oFileInfo = new FileInfo(folder + "bestGenome.xml");
doc.Save(oFileInfo.FullName);
}
public static void ThreeDHyperNEAT()
{
if (!cmdParser.IsArgumentProvided("-shape", out Program.Shape))
{
Program.Shape = "triangle";
}
if (!cmdParser.IsArgumentProvided("-folder", out Program.LogFolder))
{
Program.LogFolder = "TestLogs";
}
if (!Directory.Exists(Program.LogFolder))
{
Directory.CreateDirectory(Program.LogFolder);
}
if (!cmdParser.IsIntArgumentProvided("-gens", out Program.MaxGenerations))
{
Program.MaxGenerations = 1000;
}
double maxFitness = 0;
int maxGenerations = Program.MaxGenerations;
int populationSize = Program.PopulationSize;
IExperiment exp = new Skirmish3DExperiment(5, Program.Shape, Program.PopulationSize);
StreamWriter sw = File.CreateText(Path.Combine(Program.LogFolder,
String.Format("{0}-logfile.log", Program.LogFolder)));
sw.AutoFlush = true;
XmlDocument doc;
FileInfo oFileInfo;
IdGenerator idgen;
EvolutionAlgorithm ea;
idgen = new IdGenerator();
ea = new EvolutionAlgorithm(new Population(idgen, GenomeFactory.CreateGenomeList(exp.DefaultNeatParameters, idgen, exp.InputNeuronCount, exp.OutputNeuronCount, exp.DefaultNeatParameters.pInitialPopulationInterconnections, populationSize)), exp.PopulationEvaluator, exp.DefaultNeatParameters);
for (int j = 0; j < maxGenerations; j++)
{
DateTime dt = DateTime.Now;
ea.PerformOneGeneration();
if (ea.BestGenome.Fitness > maxFitness)
{
maxFitness = ea.BestGenome.Fitness;
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome);
oFileInfo = new FileInfo(Path.Combine(Program.LogFolder, "BestGenome-" + j.ToString() + ".xml"));
doc.Save(oFileInfo.FullName);
// This will output the substrate, uncomment if you want that
/* doc = new XmlDocument();
* XmlGenomeWriterStatic.Write(doc, (NeatGenome) SkirmishNetworkEvaluator.substrate.generateMultiGenomeModulus(ea.BestGenome.Decode(null),5));
* oFileInfo = new FileInfo(folder + "bestNetwork" + j.ToString() + ".xml");
* doc.Save(oFileInfo.FullName);
*/
}
Console.WriteLine(ea.Generation.ToString() + " " + ea.BestGenome.Fitness + " " + (DateTime.Now.Subtract(dt)));
//Do any post-hoc stuff here
sw.WriteLine("{0} {1} {2}", ea.Generation, maxFitness, ea.Population.MeanFitness);
sw.Flush();
}
sw.Close();
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome, ActivationFunctionFactory.GetActivationFunction("NullFn"));
oFileInfo = new FileInfo(Path.Combine(Program.LogFolder, "BestGenome.xml"));
doc.Save(oFileInfo.FullName);
}
private static void PredatorCCEAHNMainThread(object oAgentId)
{
int agentId = (int)oAgentId;
double maxFitness = 0;
int maxGenerations = Program.MaxGenerations;
int populationSize = Program.PopulationSize;
IExperiment exp = new SkirmishCCEAExperiment(agentId, Program.PopulationSize);
StreamWriter sw = File.CreateText(Path.Combine(Program.LogFolder,
String.Format("{0}-logfile-{1}.log", Program.LogFolder, agentId)));
sw.AutoFlush = true;
XmlDocument doc;
FileInfo oFileInfo;
IdGenerator idgen = new IdGenerator();
EvolutionAlgorithm ea = new EvolutionAlgorithm(
new Population(idgen,
GenomeFactory.CreateGenomeList(exp.DefaultNeatParameters,
idgen, exp.InputNeuronCount, exp.OutputNeuronCount,
exp.DefaultNeatParameters.pInitialPopulationInterconnections,
populationSize)),
exp.PopulationEvaluator, exp.DefaultNeatParameters);
for (int j = 0; j < maxGenerations; j++)
{
DateTime dt = DateTime.Now;
ea.PerformOneGeneration();
if (ea.BestGenome.Fitness > maxFitness)
{
maxFitness = ea.BestGenome.Fitness;
doc = new XmlDocument();
XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome);
oFileInfo = new FileInfo(Path.Combine(LogFolder,
String.Format("BestGenome-{0}-{1}.xml", agentId, j)));
doc.Save(oFileInfo.FullName);
// This will output the substrate, uncomment if you want that
/* doc = new XmlDocument();
* XmlGenomeWriterStatic.Write(doc, (NeatGenome) SkirmishNetworkEvaluator.substrate.generateMultiGenomeModulus(ea.BestGenome.Decode(null),5));
* oFileInfo = new FileInfo(folder + "bestNetwork" + j.ToString() + ".xml");
* doc.Save(oFileInfo.FullName);
*/
}
Console.WriteLine("[{0}] {1} {2} {3}", agentId, ea.Generation, ea.BestGenome.Fitness, (DateTime.Now.Subtract(dt)));
//Do any post-hoc stuff here
sw.WriteLine("{0} {1} {2}", ea.Generation, maxFitness, ea.Population.MeanFitness);
sw.Flush();
}
sw.Close();
//doc = new XmlDocument();
//XmlGenomeWriterStatic.Write(doc, (NeatGenome)ea.BestGenome, ActivationFunctionFactory.GetActivationFunction("NullFn"));
//oFileInfo = new FileInfo(Path.Combine(LogFolder, "BestGenome.xml"));
//doc.Save(oFileInfo.FullName);
Environment.Exit(0);
}