public GameAINeuroEvolutionaryLearning(int size, FileStream file)
{
population = new List <Strategy>();
this.size = size;
rand = new ThreadSafeRandom();
Strategy strategy = (Strategy)Network.Load(file);
population.Add(strategy);
for (int i = 0; i < size - 1; i++)
{
population.Add(strategy.CreateNew());
}
}
public void Regenerate()
{
Strategy ancestor = population[0];
// clear population
population.Clear();
// add chromosomes to the population
for (int i = 0; i < size; i++)
{
// create new chromosome
Strategy c = ancestor.CreateNew();
// calculate it's fitness
// add it to population
population.Add(c);
}
Evaluate();
}
public GameAINeuroEvolutionaryLearning(int size)
{
population = new List <Strategy>();
this.size = size;
rand = new ThreadSafeRandom();
Strategy strategy = new Strategy(
//new SigmoidFunction(),
new LineFunction(),
Settings.MAX_CHESSES,
Settings.NETWORK_STRUCT);
population.Add(strategy);
for (int i = 0; i < size - 1; i++)
{
population.Add(strategy.CreateNew());
}
}
public GameAINeuroEvolutionaryLearning(int size)
{
population = new List<Strategy>();
this.size = size;
rand = new ThreadSafeRandom();
Strategy strategy = new Strategy(
//new SigmoidFunction(),
new LineFunction(),
Settings.MAX_CHESSES,
Settings.NETWORK_STRUCT);
population.Add(strategy);
for (int i = 0; i < size - 1; i++)
{
population.Add(strategy.CreateNew());
}
}