/// <summary>
/// Create a Feedforward Network with the given number of layers and neurons filled with the given weights from the genome
/// </summary>
/// <param name="inputs">Number of input neurons</param>
/// <param name="outputNeurons">Number of output neurons</param>
/// <param name="hiddenLayers">Number of hidden neuron layers</param>
/// <param name="neuronsPerHiddenLayer">Number of neurons per hidden layer</param>
public FeedforwardNetwork(int inputs, int outputNeurons, int hiddenLayers, int neuronsPerHiddenLayer, Genome genome)
{
InputNeuronCount = inputs;
OutputNeuronCount = outputNeurons;
Genome = genome;
var allweights = genome.Chromosome;
var lastOutputCount = setHiddenLayers(inputs, hiddenLayers, neuronsPerHiddenLayer, allweights);
var usedWeightCount = _hiddenLayers.Sum(x => x.AllWeights.Count());
_outputLayer = new NeuronLayer(outputNeurons, lastOutputCount, allweights.Skip(usedWeightCount));
}
/// <summary>
/// Create a Feedforward Network with the given number of layers and neurons filled with the given weights from the genome
/// </summary>
/// <param name="inputs">Number of input neurons</param>
/// <param name="outputNeurons">Number of output neurons</param>
/// <param name="hiddenLayers">Number of hidden neuron layers</param>
/// <param name="neuronsPerHiddenLayer">Number of neurons per hidden layer</param>
public FeedforwardNetwork(int inputs, int outputNeurons, int hiddenLayers, int neuronsPerHiddenLayer, Genome genome)
{
InputNeuronCount = inputs;
OutputNeuronCount = outputNeurons;
Genome = genome;
var allweights = genome.Chromosome;
var lastOutputCount = setHiddenLayers(inputs, hiddenLayers, neuronsPerHiddenLayer, allweights);
var usedWeightCount = _hiddenLayers.Sum(x => x.AllWeights.Count());
_outputLayer = new NeuronLayer(outputNeurons, lastOutputCount, allweights.Skip(usedWeightCount));
}
/// <summary>
/// Create a Feedforward Network with the given number of layers and neurons, a random genome will be created
/// </summary>
/// <param name="inputs">Number of input neurons</param>
/// <param name="outputNeurons">Number of output neurons</param>
/// <param name="hiddenLayers">Number of hidden neuron layers</param>
/// <param name="neuronsPerHiddenLayer">Number of neurons per hidden layer</param>
public FeedforwardNetwork(int inputs, int outputNeurons, int hiddenLayers, int neuronsPerHiddenLayer)
{
InputNeuronCount = inputs;
OutputNeuronCount = outputNeurons;
var lastOutputCount = setHiddenLayers(inputs, hiddenLayers, neuronsPerHiddenLayer);
_outputLayer = new NeuronLayer(outputNeurons, lastOutputCount);
var allWeights = new List<double>();
foreach (var layer in _hiddenLayers)
{
allWeights.AddRange(layer.AllWeights);
}
allWeights.AddRange(_outputLayer.AllWeights);
Genome = new Genome(allWeights, 0.0);
}
/// <summary>
/// Create a Feedforward Network with the given number of layers and neurons, a random genome will be created
/// </summary>
/// <param name="inputs">Number of input neurons</param>
/// <param name="outputNeurons">Number of output neurons</param>
/// <param name="hiddenLayers">Number of hidden neuron layers</param>
/// <param name="neuronsPerHiddenLayer">Number of neurons per hidden layer</param>
public FeedforwardNetwork(int inputs, int outputNeurons, int hiddenLayers, int neuronsPerHiddenLayer)
{
InputNeuronCount = inputs;
OutputNeuronCount = outputNeurons;
var lastOutputCount = setHiddenLayers(inputs, hiddenLayers, neuronsPerHiddenLayer);
_outputLayer = new NeuronLayer(outputNeurons, lastOutputCount);
var allWeights = new List <double>();
foreach (var layer in _hiddenLayers)
{
allWeights.AddRange(layer.AllWeights);
}
allWeights.AddRange(_outputLayer.AllWeights);
Genome = new Genome(allWeights, 0.0);
}
private int setHiddenLayers(int inputs, int hiddenLayers, int neuronsPerHiddenLayer)
{
_hiddenLayers = new List <NeuronLayer>();
_stateLayers = new List <NeuronLayer>();
var lastOutputCount = inputs;
for (int layerIndex = 0; layerIndex < hiddenLayers; layerIndex++)
{
var stateLayer = new NeuronLayer(neuronsPerHiddenLayer, inputsPerNeuron: 1, randomInputWeights: false);
_stateLayers.Add(stateLayer);
var inputForHiddenLayer = lastOutputCount + neuronsPerHiddenLayer;
var hiddenLayer = new NeuronLayer(neuronsPerHiddenLayer, inputForHiddenLayer);
_hiddenLayers.Add(hiddenLayer);
lastOutputCount = neuronsPerHiddenLayer;
}
return(lastOutputCount);
}
private int setHiddenLayers(int inputs, int hiddenLayers, int neuronsPerHiddenLayer)
{
_hiddenLayers = new List<NeuronLayer>();
_stateLayers = new List<NeuronLayer>();
var lastOutputCount = inputs;
for (int layerIndex = 0; layerIndex < hiddenLayers; layerIndex++)
{
var stateLayer = new NeuronLayer(neuronsPerHiddenLayer, inputsPerNeuron: 1, randomInputWeights: false);
_stateLayers.Add(stateLayer);
var inputForHiddenLayer = lastOutputCount + neuronsPerHiddenLayer;
var hiddenLayer = new NeuronLayer(neuronsPerHiddenLayer, inputForHiddenLayer);
_hiddenLayers.Add(hiddenLayer);
lastOutputCount = neuronsPerHiddenLayer;
}
return lastOutputCount;
}
