Example #1
0
        /// <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.
            KeepawayEvaluator evaluator = new KeepawayEvaluator();

            // 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);
            //IGenomeListEvaluator<NeatGenome> genomeListEvaluator = new ParallelGenomeListEvaluator<NeatGenome, IBlackBox>(genomeDecoder, evaluator);
            IGenomeListEvaluator <NeatGenome> genomeListEvaluator = new SerialGenomeListEvaluator <NeatGenome, IBlackBox>(genomeDecoder, evaluator, true);

            // Initialize the evolution algorithm.
            ea.Initialize(genomeListEvaluator, genomeFactory, genomeList);

            // Finished. Return the evolution algorithm
            return(ea);
        }
Example #2
0
        /// <summary>
        /// Initialize the experiment with some optional XML configutation data.
        /// </summary>
        public void Initialize(string name, XmlElement xmlConfig)
        {
            _name                    = name;
            _populationSize          = XmlUtils.GetValueAsInt(xmlConfig, "PopulationSize");
            _specieCount             = XmlUtils.GetValueAsInt(xmlConfig, "SpecieCount");
            _transfer                = XmlUtils.GetValueAsBool(xmlConfig, "Transfer");
            _seed                    = XmlUtils.GetValueAsBool(xmlConfig, "Seed");
            _activationScheme        = ExperimentUtils.CreateActivationScheme(xmlConfig, "Activation");
            _complexityRegulationStr = XmlUtils.TryGetValueAsString(xmlConfig, "ComplexityRegulationStrategy");
            _complexityThreshold     = XmlUtils.TryGetValueAsInt(xmlConfig, "ComplexityThreshold");

            _trialsPerEvaluation  = XmlUtils.GetValueAsInt(xmlConfig, "TrialsPerEvaluation");
            _description          = XmlUtils.TryGetValueAsString(xmlConfig, "Description");
            _parallelOptions      = ExperimentUtils.ReadParallelOptions(xmlConfig);
            _eaParams             = new NeatEvolutionAlgorithmParameters();
            _eaParams.SpecieCount = _specieCount;
            _neatGenomeParams     = new NeatGenomeParameters();
        }