/// <summary> /// Create and return a NeatEvolutionAlgorithm object ready for running the NEAT algorithm/search. Various sub-parts /// of the algorithm are also constructed and connected up. /// This overload accepts a pre-built genome population and their associated/parent genome factory. /// </summary> public NeatEvolutionAlgorithm<NeatGenome> CreateEvolutionAlgorithm(IGenomeFactory<NeatGenome> genomeFactory, List<NeatGenome> genomeList) { // Create distance metric. Mismatched genes have a fixed distance of 10; for matched genes the distance is their weigth difference. IDistanceMetric distanceMetric = new ManhattanDistanceMetric(1.0, 0.0, 10.0); ISpeciationStrategy<NeatGenome> speciationStrategy = new ParallelKMeansClusteringStrategy<NeatGenome>(distanceMetric, _parallelOptions); // Create complexity regulation strategy. IComplexityRegulationStrategy complexityRegulationStrategy = ExperimentUtils.CreateComplexityRegulationStrategy(_complexityRegulationStr, _complexityThreshold); // Create the evolution algorithm. NeatEvolutionAlgorithm<NeatGenome> ea = new NeatEvolutionAlgorithm<NeatGenome>(_eaParams, speciationStrategy, complexityRegulationStrategy); // Create IBlackBox evaluator. PreyCaptureEvaluator evaluator = new PreyCaptureEvaluator(_trialsPerEvaluation, _gridSize, _preyInitMoves, _preySpeed, _sensorRange, _maxTimesteps); // Create genome decoder. IGenomeDecoder<NeatGenome, IBlackBox> genomeDecoder = CreateGenomeDecoder(); // TODO: evaulation scheme that re-evaulates existing genomes and takes average over time. // Create a genome list evaluator. This packages up the genome decoder with the genome evaluator. IGenomeListEvaluator<NeatGenome> genomeListEvaluator = new ParallelGenomeListEvaluator<NeatGenome, IBlackBox>(genomeDecoder, evaluator, _parallelOptions); // Initialize the evolution algorithm. ea.Initialize(genomeListEvaluator, genomeFactory, genomeList); // Finished. Return the evolution algorithm return ea; }
/// <summary> /// Create and return a NeatEvolutionAlgorithm object ready for running the NEAT algorithm/search. Various sub-parts /// of the algorithm are also constructed and connected up. /// This overload accepts a pre-built genome population and their associated/parent genome factory. /// </summary> public NeatEvolutionAlgorithm<NeatGenome> CreateEvolutionAlgorithm(IGenomeFactory<NeatGenome> genomeFactory, List<NeatGenome> genomeList) { // Create distance metric. Mismatched genes have a fixed distance of 10; for matched genes the distance is their weigth difference. IDistanceMetric distanceMetric = new ManhattanDistanceMetric(1.0, 0.0, 10.0); ISpeciationStrategy<NeatGenome> speciationStrategy = new ParallelKMeansClusteringStrategy<NeatGenome>(distanceMetric, _parallelOptions); // Create complexity regulation strategy. IComplexityRegulationStrategy complexityRegulationStrategy = ExperimentUtils.CreateComplexityRegulationStrategy(_complexityRegulationStr, _complexityThreshold); // Create the evolution algorithm. NeatEvolutionAlgorithm<NeatGenome> ea = new NeatEvolutionAlgorithm<NeatGenome>(_eaParams, speciationStrategy, complexityRegulationStrategy); // Create IBlackBox evaluator. BinaryElevenMultiplexerEvaluator evaluator = new BinaryElevenMultiplexerEvaluator(); // Create genome decoder. IGenomeDecoder<NeatGenome, IBlackBox> genomeDecoder = CreateGenomeDecoder(); // Create a genome list evaluator. This packages up the genome decoder with the genome evaluator. IGenomeListEvaluator<NeatGenome> innerEvaluator = new ParallelGenomeListEvaluator<NeatGenome, IBlackBox>(genomeDecoder, evaluator, _parallelOptions); // Wrap the list evaluator in a 'selective' evaulator that will only evaluate new genomes. That is, we skip re-evaluating any genomes // that were in the population in previous generations (elite genomes). This is determiend by examining each genome's evaluation info object. IGenomeListEvaluator<NeatGenome> selectiveEvaluator = new SelectiveGenomeListEvaluator<NeatGenome>( innerEvaluator, SelectiveGenomeListEvaluator<NeatGenome>.CreatePredicate_OnceOnly()); // Initialize the evolution algorithm. ea.Initialize(selectiveEvaluator, genomeFactory, genomeList); // Finished. Return the evolution algorithm return ea; }
/// <summary> /// Create and return a NeatEvolutionAlgorithm object ready for running the NEAT algorithm/search. Various sub-parts /// of the algorithm are also constructed and connected up. /// This overload accepts a pre-built genome population and their associated/parent genome factory. /// </summary> public NeatEvolutionAlgorithm<NeatGenome> CreateEvolutionAlgorithm(IGenomeFactory<NeatGenome> genomeFactory, List<NeatGenome> genomeList) { // Create distance metric. Mismatched genes have a fixed distance of 10; for matched genes the distance is their weigth difference. IDistanceMetric distanceMetric = new ManhattanDistanceMetric(1.0, 0.0, 10.0); ISpeciationStrategy<NeatGenome> speciationStrategy = new ParallelKMeansClusteringStrategy<NeatGenome>(distanceMetric, _parallelOptions); // Create complexity regulation strategy. IComplexityRegulationStrategy complexityRegulationStrategy = ExperimentUtils.CreateComplexityRegulationStrategy(_complexityRegulationStr, _complexityThreshold); // Create the evolution algorithm. NeatEvolutionAlgorithm<NeatGenome> ea = new NeatEvolutionAlgorithm<NeatGenome>(_eaParams, speciationStrategy, complexityRegulationStrategy); // Create IBlackBox evaluator. DoublePoleBalancingEvaluator evaluator; switch(_variantStr) { case "DoublePole": evaluator = new DoublePoleBalancingEvaluator(); break; case "DoublePoleNv": evaluator = new DoublePoleBalancingEvaluatorNv(); break; case "DoublePoleNvAntiWiggle": evaluator = new DoublePoleBalancingEvaluatorNvAntiWiggle(); break; default: throw new SharpNeatException(string.Format("DoublePoleBalancing experiment config XML specifies unknown variant [{0}]", _variantStr)); } // Create genome decoder. IGenomeDecoder<NeatGenome, IBlackBox> genomeDecoder = CreateGenomeDecoder(); // Create a genome list evaluator. This packages up the genome decoder with the genome evaluator. IGenomeListEvaluator<NeatGenome> innerEvaluator = new ParallelGenomeListEvaluator<NeatGenome, IBlackBox>(genomeDecoder, evaluator, _parallelOptions); // Wrap the list evaluator in a 'selective' evaulator that will only evaluate new genomes. That is, we skip re-evaluating any genomes // that were in the population in previous generations (elite genomes). This is determiend by examining each genome's evaluation info object. IGenomeListEvaluator<NeatGenome> selectiveEvaluator = new SelectiveGenomeListEvaluator<NeatGenome>( innerEvaluator, SelectiveGenomeListEvaluator<NeatGenome>.CreatePredicate_OnceOnly()); // Initialize the evolution algorithm. ea.Initialize(selectiveEvaluator, genomeFactory, genomeList); // Finished. Return the evolution algorithm return ea; }