public IGeneticAlgorithm Create(NeuralNetworkConfigurationSettings networkConfig, GenerationConfigurationSettings generationConfig, EvolutionConfigurationSettings evolutionConfig)
{
var breeder = _breederFactory.Create();
var mutator = _mutatorFactory.Create();
var workingSet = _workingSetFactory.Create();
return GeneticAlgorithm.GetInstance(networkConfig, generationConfig, evolutionConfig, _networkFactory, breeder, mutator, workingSet, _evaluatableFactory, null);
}
static void Main(string[] args)
{
NeuralNetworkConfigurationSettings networkConfig = new NeuralNetworkConfigurationSettings
{
NumInputNeurons = 1,
NumOutputNeurons = 1,
NumHiddenLayers = 2,
NumHiddenNeurons = 3,
SummationFunction = new SimpleSummation(),
ActivationFunction = new TanhActivationFunction()
};
GenerationConfigurationSettings generationSettings = new GenerationConfigurationSettings
{
UseMultithreading = true,
GenerationPopulation = 500
};
EvolutionConfigurationSettings evolutionSettings = new EvolutionConfigurationSettings
{
NormalMutationRate = 0.05,
HighMutationRate = 0.5,
GenerationsPerEpoch = 10,
NumEpochs = 1000,
NumTopEvalsToReport = 10
};
MutationConfigurationSettings mutationSettings = new MutationConfigurationSettings
{
MutateAxonActivationFunction = true,
MutateNumberOfHiddenLayers = true,
MutateNumberOfHiddenNeuronsInLayer = true,
MutateSomaBiasFunction = true,
MutateSomaSummationFunction = true,
MutateSynapseWeights = true
};
var random = new RandomWeightInitializer(new Random());
INeuralNetworkFactory factory = NeuralNetworkFactory.GetInstance(SomaFactory.GetInstance(networkConfig.SummationFunction), AxonFactory.GetInstance(networkConfig.ActivationFunction), SynapseFactory.GetInstance(new RandomWeightInitializer(new Random()), AxonFactory.GetInstance(networkConfig.ActivationFunction)), SynapseFactory.GetInstance(new ConstantWeightInitializer(1.0), AxonFactory.GetInstance(new IdentityActivationFunction())), random);
IBreeder breeder = BreederFactory.GetInstance(factory, random).Create();
IMutator mutator = MutatorFactory.GetInstance(factory, random).Create(mutationSettings);
IEvalWorkingSet history = EvalWorkingSetFactory.GetInstance().Create(50);
IEvaluatableFactory evaluatableFactory = new GameEvaluationFactory();
IStorageProxy proxy = new NodeJSProxy(1, "http://localhost:3000", "123456789");
IEpochAction action = new BestPerformerUpdater(proxy);
var GAFactory = GeneticAlgorithmFactory.GetInstance(evaluatableFactory);
IGeneticAlgorithm evolver = GAFactory.Create(networkConfig, generationSettings, evolutionSettings, factory, breeder, mutator, history, evaluatableFactory, action);
evolver.RunSimulation();
}
public IGeneticAlgorithm Create(NeuralNetworkConfigurationSettings networkConfig)
{
var breeder = _breederFactory.Create();
var mutator = _mutatorFactory.Create();
var workingSet = _workingSetFactory.Create();
var generationConfig = new GenerationConfigurationSettings
{
GenerationPopulation = 100,
UseMultithreading = true
};
var evolutionConfig = new EvolutionConfigurationSettings
{
GenerationsPerEpoch = 100,
HighMutationRate = 0.5,
NormalMutationRate = 0.05,
NumEpochs = 10
};
return GeneticAlgorithm.GetInstance(networkConfig, generationConfig, evolutionConfig, _networkFactory, breeder, mutator, workingSet, _evaluatableFactory, null);
}
public IGeneticAlgorithm Create(NeuralNetworkConfigurationSettings networkConfig, GenerationConfigurationSettings generationConfig, EvolutionConfigurationSettings evolutionConfig, INeuralNetworkFactory networkFactory, IBreeder breeder, IMutator mutator, IEvalWorkingSet workingSet, IEvaluatableFactory evaluatableFactory, IEpochAction epochAction)
{
return GeneticAlgorithm.GetInstance(networkConfig, generationConfig, evolutionConfig, _networkFactory, breeder, mutator, workingSet, _evaluatableFactory, epochAction);
}
