public FullyConnectedNeuralNetworkModel[] CreateNextGeneration(FullyConnectedNeuralNetworkModel[] parents, int populationSize)
{
var children = new FullyConnectedNeuralNetworkModel[populationSize - parents.Length];
var indexesBred = new ConcurrentDictionary <int, List <int> >();
Parallel.For(0, children.Length, childIndex =>
{
var motherIndex = 0;
var fatherIndex = 0;
var motherHasChildren = false;
while (motherIndex == fatherIndex || motherHasChildren && indexesBred[motherIndex].Contains(fatherIndex))
{
var parentIndexes = new[] { random.Next(parents.Length), random.Next(parents.Length) }.OrderBy(i => i);
motherIndex = parentIndexes.ElementAt(0);
fatherIndex = parentIndexes.ElementAt(1);
motherHasChildren = indexesBred.ContainsKey(motherIndex);
}
children[childIndex] = modelBreeder.Breed(parents[motherIndex], parents[fatherIndex]);
indexesBred.AddOrUpdate(motherIndex, new List <int>()
{
fatherIndex
}, (key, value) =>
{
value.Add(fatherIndex);
return(value);
});
});
return(children);
}
public FullyConnectedNeuralNetworkModel[] CreateNextGeneration(FullyConnectedNeuralNetworkModel[] parents, int populationSize)
{
var children = new List <FullyConnectedNeuralNetworkModel>();
var remainingParentIndexes = Enumerable.Range(0, parents.Length).ToList();
while (children.Count < populationSize - parents.Length)
{
var randomRemainingParentIndex = random.Next(1, remainingParentIndexes.Count);
var motherIndex = remainingParentIndexes[0];
var fatherIndex = remainingParentIndexes[randomRemainingParentIndex];
var child = modelBreeder.Breed(parents[motherIndex], parents[fatherIndex]);
children.Add(child);
remainingParentIndexes.Remove(motherIndex);
remainingParentIndexes.Remove(fatherIndex);
}
return(children.ToArray());
}
