/// <summary>
/// 基因交叉操作，单点交叉
/// </summary>
public static void CompleteCrossover(Genotype parent1, Genotype parent2, float swapChance, out Genotype offspring1, out Genotype offspring2)
{
int parameterCount = parent1.ParameterCount;
float[] off1Parameters = new float[parameterCount];
float[] off2Parameters = new float[parameterCount];
//遍历所有参数，随机交换
for (int i = 0; i < parameterCount; i++)
{
//如果生成的随机数小于交换参考值，则进行交换
if (MathHelper.RandomNext() < swapChance)
{
//交互参数
off1Parameters[i] = parent2[i];
off2Parameters[i] = parent1[i];
}
else
{
//不进行交换，直接遗传到子基因
off1Parameters[i] = parent1[i];
off2Parameters[i] = parent2[i];
}
}
//根据新的参数矩阵生成新的基于型
offspring1 = new Genotype(off1Parameters);
offspring2 = new Genotype(off2Parameters);
}
/// <summary>
/// 基因变异操作
/// </summary>
public static void MutateGenotype(Genotype genotype, float mutationProb, float mutationAmount)
{
//mutationProb 一个参数被突变的概率
//mutationAmount 默认的变异参数
for (int i = 0; i < genotype.ParameterCount; i++)
{
if (MathHelper.RandomNext() < mutationProb)
{
//控制变异后的参数在一定的量内
genotype[i] += (float)(MathHelper.RandomNext() * (mutationAmount * 2) - mutationAmount);
}
}
}
/// <summary>
/// 构造遗传代理
/// </summary>
/// <param name="_genotype">基因</param>
/// <param name="_activation">激活函数</param>
/// <param name="_topogy">拓扑结构</param>
public Agent(Genotype _genotype, NeuralLayer.ActivationFunction _activation, params uint[] _topogy)
{
Genotype = _genotype;
FNN = new NeuralNetwork(_topogy);
foreach (NeuralLayer layer in FNN.Layers)
{
layer.NeuronActivationFunction = _activation;
}
if(FNN.WeightCount != _genotype.ParameterCount)
throw new ArgumentException("WeightCount != Topology");
//使用基因参数初始化神经网络
IEnumerator<float> parameters = _genotype.GetEnumerator();
foreach (NeuralLayer layer in FNN.Layers)
{
for (int i = 0; i < layer.Weights.GetLength(0); i++)
{
for (int j = 0; j < layer.Weights.GetLength(1); j++)
{
layer.Weights[i, j] = parameters.Current;
parameters.MoveNext();
}
}
}
}
public int CompareTo(Agent other)
{
return Genotype.CompareTo(other.Genotype);
}
