public AdjustedNeuralNetworkPopulation Create(NeuralNetwork network, NeuralNetworkTest test, out AdjustedNeuralNetworkBodyFactory bodyFactory)
{
Contract.Requires(network != null);
Contract.Requires(test != null);
return DoCreate(network, test, out bodyFactory);
}
public static void Begin()
{
//var parameters = new AdjustedTestableNetworkParameters
//{
// Test = test,
// Network = NeuralArchitecture.CreateLayered(
// test.InputSize,
// test.OutputSize,
// () => new Synapse(),
// () => new ActivationNeuron(new LinearActivationFunction(1)),
// true,
// 20, 10)
//};
var parameters = new AdjustedTestableNetworkParameters
{
Test = test,
Network = NeuralArchitecture.CreateFullConnected(
test.InputSize,
test.OutputSize,
20,
() => new Synapse(),
() => new ActivationNeuron(new LinearActivationFunction(1)),
true)
};
var factory = new AdjustedNeuralNetworkBodyFactory(parameters);
factory.CrossoverChunkSize = IntRange.CreateFixed((parameters.Network.ConnectionCount + parameters.Network.NodeCount) / 2 - 1);
//factory.CrossoverChunkSize = new InclusiveRange(10, 10);
factory.PointMutationChance = 0.005;
var population = new AdjustedNeuralNetworkPopulation();
population.ChanceOfMigration = 0.1;
for (int idx = 0; idx < groupCount; idx++)
{
var group = new AdjustedNeuralNetworkGroup(
factory,
groupSize);
//group.SelectionStrategy = new RandomSelectionStrategy();
population.Groups.Add(group);
}
var context = new GAContext(population);
context.BestBodyArrived += OnBestArrived;
context.Start();
Console.ReadKey();
context.Stop();
}
private AdjustedNeuralNetworkPopulation DoCreate(NeuralNetwork network, NeuralNetworkTest test, out AdjustedNeuralNetworkBodyFactory bodyFactory)
{
var parameters = new AdjustedTestableNetworkParameters
{
Test = test,
Network = network,
MutationStrength = MutationStrength
};
bodyFactory = new AdjustedNeuralNetworkBodyFactory(parameters);
if (CrossoverChunkSize.HasValue)
{
bodyFactory.CrossoverChunkSize = CrossoverChunkSize.Value;
}
else
{
bodyFactory.CrossoverChunkSize = IntRange.CreateFixed(parameters.AdjustableItems.Length / 2 - 1);
}
bodyFactory.PointMutationChance = PointMutationChance;
var newPop = new AdjustedNeuralNetworkPopulation();
newPop.ChanceOfMigration = ChanceOfMigration;
for (int gIdx = 0; gIdx < groupCount; gIdx++)
{
var group = new AdjustedNeuralNetworkGroup(bodyFactory, groupSize);
if (SelectionStrategy != null) group.SelectionStrategy = SelectionStrategy;
newPop.Groups.Add(group);
}
return newPop;
}