// Initialize with pre-existing xml data
public void Initialize(string xmlData)
{
/*** Initialize experiment ***/
experiment = new PCGNeatExperiment() as INeatExperiment;
// Null because not reading settings from xmlFile
experiment.Initialize("PCG Conetent EA", null);
/*** Load population of genomes from xml string ***/
List <NeatGenome> genomeList;
using (XmlReader xr = XmlReader.Create(new StringReader(xmlData)))
{
genomeList = experiment.LoadPopulation(xr);
}
if (genomeList.Count == 0)
{
Debug.LogError("No genomes loaded from XML data from network. Check data is being read correctly.");
return;
}
else
{
Debug.Log("Loaded " + genomeList.Count + " Genomes");
}
/*** Create the algorithm interface ***/
contentEA = experiment.CreateEvolutionAlgorithm(genomeList[0].GenomeFactory, genomeList);
}
public void Initialize()
{
/*** Initialize experiment ***/
experiment = new PCGNeatExperiment() as INeatExperiment;
// Null because not reading settings from xmlFile
experiment.Initialize("PCG Conetent EA", null);
/*** Randomly generate population ***/
// Set initial settings
// ? means it is nullable
int?popSize = experiment.DefaultPopulationSize;
// Create a genome factory appropriate for the experiment.
IGenomeFactory <NeatGenome> genomeFactory = experiment.CreateGenomeFactory();
// Create an initial population of randomly generated genomes.
// 0u is a struct for a 32 bit unsigned integer
List <NeatGenome> genomeList = genomeFactory.CreateGenomeList(popSize.Value, 0u);
// Check number of species is <= the number of the genomes.
if (genomeList.Count < experiment.NeatEvolutionAlgorithmParameters.SpecieCount)
{
Debug.Log("Genome count must be >= specie count. Genomes=" + genomeList.Count
+ " Species=" + experiment.NeatEvolutionAlgorithmParameters.SpecieCount);
return;
}
/*** Create the algorithm interface ***/
contentEA = experiment.CreateEvolutionAlgorithm(genomeFactory, genomeList);
}
// Initialize with pre-existing xml data
public void Initialize(string xmlData, PCGSharpHighLevelFeatures originalFeatures)
{
/*** Initialize experiment ***/
experiment = new CPPNRepairExperiment() as INeatExperiment;
// Null because not reading settings from xmlFile
experiment.Initialize("PCG Conetent EA", null);
/*** Load population of genomes from xml string ***/
List <NeatGenome> genomeList;
using (XmlReader xr = XmlReader.Create(new StringReader(xmlData)))
{
genomeList = experiment.LoadPopulation(xr);
}
if (genomeList.Count == 0)
{
Debug.LogError("No genomes loaded from XML data from network. Check data is being read correctly.");
return;
}
else
{
Debug.Log("Loaded " + genomeList.Count + " Genomes");
}
Debug.Log(".........Population loaded");
((CPPNRepairExperiment)experiment).SetOriginalFeatures(originalFeatures);
Debug.Log("........Original features added to experiment");
/*** Create the algorithm interface ***/
contentEA = experiment.CreateEvolutionAlgorithm(genomeList[0].GenomeFactory, genomeList);
Debug.Log("........Content EA created");
}
public void Initialize()
{
/*** Initialize experiment ***/
experiment = new PCGNeatExperiment() as INeatExperiment;
// Null because not reading settings from xmlFile
experiment.Initialize("PCG Conetent EA",null);
/*** Randomly generate population ***/
// Set initial settings
// ? means it is nullable
int? popSize = experiment.DefaultPopulationSize;
// Create a genome factory appropriate for the experiment.
IGenomeFactory<NeatGenome> genomeFactory = experiment.CreateGenomeFactory();
// Create an initial population of randomly generated genomes.
// 0u is a struct for a 32 bit unsigned integer
List<NeatGenome> genomeList = genomeFactory.CreateGenomeList(popSize.Value, 0u);
// Check number of species is <= the number of the genomes.
if (genomeList.Count < experiment.NeatEvolutionAlgorithmParameters.SpecieCount)
{
Debug.Log("Genome count must be >= specie count. Genomes=" + genomeList.Count
+ " Species=" + experiment.NeatEvolutionAlgorithmParameters.SpecieCount);
return;
}
/*** Create the algorithm interface ***/
contentEA = experiment.CreateEvolutionAlgorithm(genomeFactory, genomeList);
}
// Initialize with pre-existing xml data
public void Initialize(string xmlData)
{
/*** Initialize experiment ***/
experiment = new PCGNeatExperiment() as INeatExperiment;
// Null because not reading settings from xmlFile
experiment.Initialize("PCG Conetent EA",null);
/*** Load population of genomes from xml string ***/
List<NeatGenome> genomeList;
using(XmlReader xr = XmlReader.Create(new StringReader(xmlData)))
{
genomeList = experiment.LoadPopulation(xr);
}
if(genomeList.Count == 0) {
Debug.LogError("No genomes loaded from XML data from network. Check data is being read correctly.");
return;
}
else
Debug.Log("Loaded " + genomeList.Count + " Genomes");
/*** Create the algorithm interface ***/
contentEA = experiment.CreateEvolutionAlgorithm(genomeList[0].GenomeFactory, genomeList);
}
static void Main(string[] args)
{
// This program expects certain command line options, that are defined as annotated properties in the NeatSimConsole.Options class
// We instantiate this class...
_options = new Options();
// ... and pass the arguments to this program to the options parser, who uses it to set the properties in 'options'.
// If the command line options are incorrect, ParseArgumentsStrict prints a help message to the screen and exits...
if (!CommandLine.Parser.Default.ParseArgumentsStrict(args, _options))
{
// ... therefore, this should really never ever happen.
throw new SystemException("Something went wrong parsing arguments.");
}
// Now, all the properties in 'options' are set.
FastRandom.__seedRng = new FastRandom(_options.Seed);
// Initialise log4net (log to console).
// XmlConfigurator.Configure(new FileInfo("log4net.properties"));
// We instatiate a remote batch simulation experiment, and use the properties set in the XML file to initialize the experiment.
// The XML file contains properties like the number of generations to run the program for, and the number of individuals in the population.
// For properties that are not set in the XML file, we initialize default values.
_experiment = new RemoteBatchSimExperiment();
var xmlConfig = new XmlDocument();
try
{
xmlConfig.Load("neatsim.config.xml");
}
catch (FileNotFoundException e)
{
Console.WriteLine(@"Could not find neatsim.config.xml. Aborting.");
return;
}
_experiment.Initialize("NeatSim", xmlConfig.DocumentElement);
// The XML file cannot contain information about the inital number of connected neurons.
// We want to initialize our population minimally, and do this by setting an absurdly small initial connections proportion.
// The number of connected input neurons will always be at least one.
// Note that there is an absurdly small chance that more than a single neuron will be connected in generation one.
_experiment.NeatGenomeParameters.InitialInterconnectionsProportion = 0.0000000000001;
// Create a genome factory with our neat genome parameters object and the appropriate number of input and output neuron genes.
_genomeFactory = _experiment.CreateGenomeFactory();
// Create an initial population of randomly generated genomes ('born' in generation 0).
_genomeList = _genomeFactory.CreateGenomeList(_options.PopulationSize, 0);
// Create evolution algorithm and attach update events.
_ea = _experiment.CreateEvolutionAlgorithm(_genomeFactory, _genomeList);
_ea.PausedEvent += (s, e) => Console.WriteLine(_ea.RunState == RunState.Paused
? @"Program is paused"
: _ea.RunState == RunState.Running
? @"Program is unpaused."
: @"Program is in unknown state...");
_neatSimLogger = new NeatSimLogger(_options.LogFileName + '_' + DateTime.Now.ToString("yyyyMMdd"));
//
var nextGeneration = _ea.CurrentGeneration;
var doneEvent = new AutoResetEvent(false);
_ea.UpdateEvent += (s, e) =>
{
if (_ea.CurrentGeneration < nextGeneration)
{
Console.WriteLine("Aborting!");
return;
}
Console.WriteLine(string.Format("gen={0:N0} bestFitness={1:N6}", _ea.CurrentGeneration, _ea.Statistics._maxFitness));
SaveChampionGenome();
_neatSimLogger.Log(_ea);
if (_ea.CurrentGeneration >= _options.Generations)
{
_ea.Stop();
_neatSimLogger.Close();
doneEvent.Set();
}
nextGeneration++;
};
// Start algorithm (it will run on a background thread).
_ea.StartContinue();
// Hit return to quit.
//Console.ReadLine();
doneEvent.WaitOne();
}
static void Main(string[] args)
{
// This program expects certain command line options, that are defined as annotated properties in the NeatSimConsole.Options class
// We instantiate this class...
_options = new Options();
// ... and pass the arguments to this program to the options parser, who uses it to set the properties in 'options'.
// If the command line options are incorrect, ParseArgumentsStrict prints a help message to the screen and exits...
if (!CommandLine.Parser.Default.ParseArgumentsStrict(args, _options))
{
// ... therefore, this should really never ever happen.
throw new SystemException("Something went wrong parsing arguments.");
}
// Now, all the properties in 'options' are set.
FastRandom.__seedRng = new FastRandom(_options.Seed);
// Initialise log4net (log to console).
// XmlConfigurator.Configure(new FileInfo("log4net.properties"));
// We instatiate a remote batch simulation experiment, and use the properties set in the XML file to initialize the experiment.
// The XML file contains properties like the number of generations to run the program for, and the number of individuals in the population.
// For properties that are not set in the XML file, we initialize default values.
_experiment = new RemoteBatchSimExperiment();
var xmlConfig = new XmlDocument();
try
{
xmlConfig.Load("neatsim.config.xml");
}
catch (FileNotFoundException e)
{
Console.WriteLine(@"Could not find neatsim.config.xml. Aborting.");
return;
}
_experiment.Initialize("NeatSim", xmlConfig.DocumentElement);
// The XML file cannot contain information about the inital number of connected neurons.
// We want to initialize our population minimally, and do this by setting an absurdly small initial connections proportion.
// The number of connected input neurons will always be at least one.
// Note that there is an absurdly small chance that more than a single neuron will be connected in generation one.
_experiment.NeatGenomeParameters.InitialInterconnectionsProportion = 0.0000000000001;
// Create a genome factory with our neat genome parameters object and the appropriate number of input and output neuron genes.
_genomeFactory = _experiment.CreateGenomeFactory();
// Create an initial population of randomly generated genomes ('born' in generation 0).
_genomeList = _genomeFactory.CreateGenomeList(_options.PopulationSize, 0);
// Create evolution algorithm and attach update events.
_ea = _experiment.CreateEvolutionAlgorithm(_genomeFactory, _genomeList);
_ea.PausedEvent += (s, e) => Console.WriteLine(_ea.RunState == RunState.Paused
? @"Program is paused"
: _ea.RunState == RunState.Running
? @"Program is unpaused."
: @"Program is in unknown state...");
_neatSimLogger = new NeatSimLogger(_options.LogFileName + '_' + DateTime.Now.ToString("yyyyMMdd"));
//
var nextGeneration = _ea.CurrentGeneration;
var doneEvent = new AutoResetEvent(false);
_ea.UpdateEvent += (s, e) =>
{
if (_ea.CurrentGeneration < nextGeneration)
{
Console.WriteLine("Aborting!");
return;
}
Console.WriteLine(string.Format("gen={0:N0} bestFitness={1:N6}", _ea.CurrentGeneration, _ea.Statistics._maxFitness));
SaveChampionGenome();
_neatSimLogger.Log(_ea);
if (_ea.CurrentGeneration >= _options.Generations)
{
_ea.Stop();
_neatSimLogger.Close();
doneEvent.Set();
}
nextGeneration++;
};
// Start algorithm (it will run on a background thread).
_ea.StartContinue();
// Hit return to quit.
//Console.ReadLine();
doneEvent.WaitOne();
}
