protected override void Mutation()
{
do
{
outputNeuron = Network.GetRandomNeuron();
inputNeuron = Network.GetRandomNeuron();
} while ((inputNeuron == outputNeuron));
insertedNeuron = new Neuron(ActivationFunc);
synapseToOutput = new Synapse(insertedNeuron)
{
Weight = NeuralHelper.GetRandomWeigth()
};
outputNeuron.InputSynapses.Add(synapseToOutput);
synapseToInput = new Synapse(inputNeuron)
{
Weight = NeuralHelper.GetRandomWeigth()
};
insertedNeuron.InputSynapses.Add(synapseToInput);
Network.Neurons.Add(insertedNeuron);
Network.Synapses.Add(synapseToOutput);
Network.Synapses.Add(synapseToInput);
}
protected override void Mutation()
{
randomSynapse = Network.GetRandomSynapse();
outputNeuron = Network.Neurons.Find(n => n.InputSynapses.Contains(randomSynapse));
inputConnection = randomSynapse._input;
insertedNeuron = new Neuron(ActivationFunc);
synapseToOutput = new Synapse(insertedNeuron)
{
Weight = NeuralHelper.GetRandomWeigth()
};
outputNeuron.InputSynapses.Add(synapseToOutput);
synapseToInput = new Synapse(inputConnection)
{
Weight = NeuralHelper.GetRandomWeigth()
};
insertedNeuron.InputSynapses.Add(synapseToInput);
outputNeuron.InputSynapses.Remove(randomSynapse);
Network.Synapses.Remove(randomSynapse);
Network.Neurons.Add(insertedNeuron);
Network.Synapses.Add(synapseToOutput);
Network.Synapses.Add(synapseToInput);
}
protected override void Mutation()
{
canImproveNext = true;
modifedSynapse = Network.GetRandomSynapse();
oldWeigth = modifedSynapse.Weight;
modifedSynapse.Weight = NeuralHelper.GetRandomWeigth();
}
protected override void Mutation()
{
//TODO: оптимизировать. Сделать добавление не только нейронов но и синапсов
Network.MetricsRecitate();
var rechoose = false;
do
{
rechoose = false;
neuronFrom = Network.GetRandomNeuron();
neuronTo = Network.GetRandomNeuron();
//Loop condition
if (neuronFrom.Distance <= neuronTo.Distance)
{
rechoose = true;
continue;
}
if (neuronTo.InputSynapses.Exists(n => n._input == neuronFrom))
{
rechoose = true;
}
} while (rechoose);
insertedSynapse = new Synapse(neuronFrom)
{
Weight = NeuralHelper.GetRandomWeigth()
};;
neuronTo.InputSynapses.Add(insertedSynapse);
Network.Synapses.Add(insertedSynapse);
Network.MetricsRecitate();
if (Network.LoopDetected())
{
Rollback();
Network.Neurons.ForEach(n => n.Reset());
}
}