/// <summary>
/// This constructor prepared the neural network by setting the hyperparameters, as well as the inputs
/// and prepares the visualization of the neural net, if an inworld spawner for the neurons is given.
/// Alpha indicates the learning rate, while it will be multiplied with alphaDecay after every learning
/// cycle to gradually decay the learning rate. alphaDecay = 1.0 disables the decay.
/// Lambda indicates a rate by which the neurons weights decay every learning cycle. This is a technique
/// to combat overfitting and exploding gradients.
/// </summary>
/// <param name="numberOfInputs">An integer indicating the number of inputs to expect</param>
/// <param name="alpha">A double representing the learning rate</param>
/// <param name="alphaDecay">A double to reduce alpha (and lambda) over time by multiplication</param>
/// <param name="lambda">A double to reduce weights by the amount of lambda multiplied with the actual weight</param>
/// <param name="debugNeuronSpawnerGameObject">A gameobject variable containing a special spawner for neuron visualization if needed</param>
public ANN(int numberOfInputs, double alpha, double alphaDecay = 1.0d, double lambda = 0.0d, GameObject debugNeuronSpawnerGameObject = null)
{
this.numInputs = numberOfInputs;
this.alpha = alpha;
this.alphaDecay = alphaDecay;
this.lambda = lambda;
// debug output visualization
debugInputNeurons = new List<GameObject>();
if (debugNeuronSpawnerGameObject != null) {
debugNeuronSpawner = debugNeuronSpawnerGameObject.GetComponent<DebugNeuronSpawner>();
for (int i = 0; i < numberOfInputs; i++) {
debugInputNeurons.Add(debugNeuronSpawner.addNeuron(i, numberOfInputs, 0));
}
}
}
public Layer(int numberOfNeurons, int numberOfInputsPerNeuron, string activationFunctionName, DebugNeuronSpawner debugNeuronSpawner)
{
if (debugNeuronSpawner != null)
{
debugNeuronSpawner.addLayer();
}
for (int i = 0; i < numberOfNeurons; i++)
{
GameObject debugNeuron = null;
if (debugNeuronSpawner != null)
{
debugNeuron = debugNeuronSpawner.addNeuron(i, numberOfNeurons, numberOfInputsPerNeuron);
}
neurons.Add(new Neuron(numberOfInputsPerNeuron, numberOfNeurons, activationFunctionName, debugNeuron));
}
}
