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; }