Evaluator for the double pole balancing task with no velocity (NV) inputs and an alternative evaluation scheme that punishes fast oscillations (anti-wiggle).
Inheritance: DoublePoleBalancingEvaluator
        /// <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);
        }
        /// <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;
        }