static void Main(string[] args)
{
// Initialise log4net (log to console).
XmlConfigurator.Configure(new FileInfo("log4net.properties"));
// Experiment classes encapsulate much of the nuts and bolts of setting up a NEAT search.
XorExperiment experiment = new XorExperiment();
// Load config XML.
XmlDocument xmlConfig = new XmlDocument();
xmlConfig.Load("xor_logging.config.xml");
experiment.Initialize("XOR", xmlConfig.DocumentElement);
// 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.
_genomeList = _genomeFactory.CreateGenomeList(150, 0);
// Create evolution algorithm and attach update event.
_ea = experiment.CreateEvolutionAlgorithm(_genomeFactory, _genomeList);
_ea.UpdateEvent += new EventHandler(ea_UpdateEvent);
// Start algorithm (it will run on a background thread).
_ea.StartContinue();
while (RunState.Terminated != _ea.RunState && RunState.Paused != _ea.RunState)
{
Thread.Sleep(2000);
}
// Hit return to quit.
//Console.ReadLine();
}
private static void Main(string[] args)
{
Debug.Assert(args != null && args.Length == 2,
"Experiment configuration file and number of runs are required!");
// Read in experiment configuration file
string experimentName = args[0];
int numRuns = Int32.Parse(args[1]);
// Initialise log4net (log to console).
XmlConfigurator.Configure(new FileInfo("log4net.properties"));
// Experiment classes encapsulate much of the nuts and bolts of setting up a NEAT search.
SteadyStateMazeNavigationNoveltyExperiment experiment = new SteadyStateMazeNavigationNoveltyExperiment();
// Load config XML.
XmlDocument xmlConfig = new XmlDocument();
xmlConfig.Load("./ExperimentConfigurations/" + experimentName);
experiment.Initialize("Novelty", xmlConfig.DocumentElement, null, null);
// 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.
_genomeList = _genomeFactory.CreateGenomeList(experiment.DefaultPopulationSize, 0);
// Create evolution algorithm and attach update event.
_ea = experiment.CreateEvolutionAlgorithm(_genomeFactory, _genomeList);
_ea.UpdateEvent += ea_UpdateEvent;
// Start algorithm (it will run on a background thread).
_ea.StartContinue();
/*while (RunState.Terminated != _ea.RunState && RunState.Paused != _ea.RunState &&
_ea.CurrentGeneration < maxGenerations)
{
Thread.Sleep(2000);
}*/
// Hit return to quit.
//Console.ReadLine();
}
/// <summary>
/// Executes a single run of the given experiment.
/// </summary>
/// <param name="genomeFactory">The factory for producing NEAT genomes.</param>
/// <param name="genomeList">The list of initial genomes (population).</param>
/// <param name="experimentName">The name of the experiment to execute.</param>
/// <param name="experiment">Reference to the initialized experiment.</param>
/// <param name="numRuns">Total number of runs being executed.</param>
/// <param name="runIdx">The current run being executed.</param>
/// <param name="startingEvaluation">
/// The number of evaluations from which execution is starting (this is only applicable in
/// the event of a restart).
/// </param>
private static void RunExperiment(IGenomeFactory<NeatGenome> genomeFactory, List<NeatGenome> genomeList,
string experimentName, BaseMazeNavigationExperiment experiment, int numRuns,
int runIdx, ulong startingEvaluation)
{
// Trap initialization exceptions (which, if applicable, could be due to initialization algorithm not
// finding a viable seed) and continue to the next run if an exception does occur
try
{
// Create evolution algorithm and attach update event.
_ea = experiment.CreateEvolutionAlgorithm(genomeFactory, genomeList, startingEvaluation);
_ea.UpdateEvent += ea_UpdateEvent;
}
catch (Exception)
{
_executionLogger.Error(string.Format("Experiment {0}, Run {1} of {2} failed to initialize",
experimentName,
runIdx + 1, numRuns));
Environment.Exit(0);
}
_executionLogger.Info(string.Format(
"Executing Experiment {0}, Run {1} of {2} from {3} starting evaluations", experimentName, runIdx + 1,
numRuns, startingEvaluation));
// Start algorithm (it will run on a background thread).
_ea.StartContinue();
while (RunState.Terminated != _ea.RunState && RunState.Paused != _ea.RunState)
{
Thread.Sleep(2000);
}
}
/// <summary>
/// Handles execution of the novelty search algorithm for comparison to each maze in the coevolution experiment.
/// </summary>
/// <returns>The end-state of the novelty search algorithm.</returns>
public INeatEvolutionAlgorithm<NeatGenome> RunNoveltySearch()
{
// Instantiate a new novelty search experiment
NoveltySearchComparisonExperiment nsExperiment = new NoveltySearchComparisonExperiment(_evaluationMazeDomain);
// Initialize the experiment
nsExperiment.Initialize(_comparisonExperimentConfig);
// Create the genome factory and generate genome list
IGenomeFactory<NeatGenome> genomeFactory = nsExperiment.CreateGenomeFactory();
List<NeatGenome> genomeList =
genomeFactory.CreateGenomeList(_comparisonExperimentConfig.Primary_PopulationSize, 0);
try
{
// Setup the algorithm and add the update event
_comparisonAlgorithm = nsExperiment.CreateEvolutionAlgorithm(genomeFactory, genomeList, 0);
_comparisonAlgorithm.UpdateEvent += ea_UpdateEvent;
}
catch (Exception)
{
_executionLogger.Error(
string.Format(
"Comparison experiment [{0}], for reference experiment [{1}] Run [{2}] of [{3}], failed to initialize",
nsExperiment.Name, _referenceExperimentName, _currentRun + 1, _totalRuns));
Environment.Exit(0);
}
_executionLogger.Info(string.Format(
"Executing comparison experiment [{0}] for reference experiment {1}, Run {2} of {3}", nsExperiment.Name,
_referenceExperimentName, _currentRun + 1,
_totalRuns));
// Start algorithm (it will run on a background thread).
_comparisonAlgorithm.StartContinue();
while (RunState.Terminated != _comparisonAlgorithm.RunState &&
RunState.Paused != _comparisonAlgorithm.RunState)
{
Thread.Sleep(2000);
}
// Return the final state of the algorithm so that statistics can be extracted
return _comparisonAlgorithm;
}