public NeuralNetwork(NeuralNetworkParameters parameters, IContinuousDistribution rng)
{
NetworkParameters = parameters;
HiddenWeights = CreateMatrix.Random <float>(NetworkParameters.HiddenLayerNeuronCount, NetworkParameters.InputCount, rng);
HiddenBiases = CreateVector.Random <float>(NetworkParameters.HiddenLayerNeuronCount, rng);
OutputWeights = CreateMatrix.Random <float>(NetworkParameters.OutputCount, NetworkParameters.HiddenLayerNeuronCount, rng);
OutputBiases = CreateVector.Random <float>(NetworkParameters.OutputCount, rng);
}
public void Initialize()
{
var inputCountDistribution = new DiscreteUniform(1 + AlgorithmParameters.MinSensorCount, 1 + AlgorithmParameters.MaxSensorCount);
var hiddenNeuronCountDistribution = new DiscreteUniform(AlgorithmParameters.MinHiddenLayerNeuronCount, AlgorithmParameters.MaxHiddenLayerNeuronCount);
for (int i = 0; i < AlgorithmParameters.PopulationCount; i++)
{
var networkParameters = new NeuralNetworkParameters()
{
InputCount = AlgorithmParameters.EvolveNetworkTopology ? inputCountDistribution.Sample() : AlgorithmParameters.MinSensorCount + 1,
HiddenLayerNeuronCount = AlgorithmParameters.EvolveNetworkTopology ? hiddenNeuronCountDistribution.Sample() : AlgorithmParameters.MinHiddenLayerNeuronCount,
OutputCount = 2,
HiddenLayerActivationFunction = AlgorithmParameters.NeuralNetworkHiddenLayerActivationFunction,
OutputLayerActivationFunction = AlgorithmParameters.NeuralNetworkOutputLayerActivationFunction
};
Population.Add(new NeuralNetwork(networkParameters, AlgorithmParameters.NeuralNetworkWeightInitializationDistribution));
}
}
