public GeneticAlgorithm(IFittnessFunction <T> fittnessFunction, ISelection <T> selection, ICrossover <T> crossover,
IMutation <T> mutation, ITerminate <T> terminate)
{
Population = new List <IChromosome <T> >();
FittnessFunction = fittnessFunction;
Selection = selection;
Crossover = crossover;
Mutation = mutation;
Terminate = terminate;
}
public NeuroGeneticAlgorithm(IFittnessFunction <Neuron> fittnessFunction, ISelection <Neuron> selection,
ICrossover <Neuron> crossover, IMutation <Neuron> mutation,
ITerminate <Neuron> terminate, NeuralNetwork networkForTeach)
: base(fittnessFunction, selection, crossover, mutation, terminate)
{
NeuralNetwork = networkForTeach;
Random = new Random((int)DateTime.Now.Ticks);
generateNeuroPopulation_();
var options = new EnvironmentOptions
{
AgentsCount = Population.Count,
FoodCount = 5,
FieldWidth = 200,
FieldHeight = 200
};
TestGameEnvironment = new GameEnvironment(options);
}