public RobotChromosome(RobotEvolutionConfiguration config)
{
Config = config;
var phenotypeEntities = new BehaviorPhenotypeEntity[config.BehaviorCount];
for (int i = 0; i < phenotypeEntities.Length; i++)
{
phenotypeEntities[i] = new BehaviorPhenotypeEntity(config, i);
}
SetPhenotypes(phenotypeEntities);
CreateGenes();
}
public RobotFitness(Func <RobotChromosome, Task <ContestGame> > contestFactoryAsync,
RobotEvolutionConfiguration config)
{
this.ContestFactoryAsync = contestFactoryAsync;
this.RobotEvolutionConfiguration = config;
}
public GeneticAlgorithm CreateGA(Func <RobotChromosome, Task <ContestGame> > contestFactory, RobotEvolutionConfiguration config)
{
NumberOfSimultaneousEvaluations = 2;
var fitness = new RobotFitness(contestFactory, config);
var chromosome = new RobotChromosome(config);
var crossover = new UniformCrossover();
var mutation = new FlipBitMutation();
var selection = new EliteSelection();
var population = new Population(NumberOfSimultaneousEvaluations, NumberOfSimultaneousEvaluations, chromosome)
{
GenerationStrategy = new PerformanceGenerationStrategy()
};
var ga = new GeneticAlgorithm(population, fitness, selection, crossover, mutation)
{
Termination = new RobotTermination(),
//TaskExecutor = new LinearTaskExecutor(),
TaskExecutor = new ParallelTaskExecutor
{
MaxThreads = 10
}
};
ga.GenerationRan += delegate
{
Console.WriteLine("Generation complete");
};
ga.MutationProbability = .1f;
return(ga);
}