public Population(int count)
{
Generation = 0;
Players = new List <PopulationItem> ();
for (int i = 0; i < count; i++)
{
var item = new PopulationItem();
item.Player = AIGeneticPlayer.CreateRandom();
Players.Add(item);
}
}
public override Player Clone()
{
AIGeneticPlayer clone = new AIGeneticPlayer();
clone._whereToGoDecider = _whereToGoDecider.Clone();
clone._humansCountDecider = _humansCountDecider.Clone();
clone._useAnyResourceFromTopCardDecider = _useAnyResourceFromTopCardDecider.Clone();
clone._resourceFromTopCardDecider = _resourceFromTopCardDecider.Clone();
clone._resourceFromCharityDecider = _resourceFromCharityDecider.Clone();
clone._resourceFromInstrumentsDecider = _resourceFromInstrumentsDecider.Clone();
clone._leaveHungryDecider = _leaveHungryDecider.Clone();
return(clone);
}
public static AIGeneticPlayer CreateRandom()
{
AIGeneticPlayer player = new AIGeneticPlayer();
player._whereToGoDecider = GetRandomDecider(WhereToGoInputsCount, AdditionalNeuronsCount, 16);
player._humansCountDecider = GetRandomDecider(GetUsedHumansInputsCount, AdditionalNeuronsCount, 9);
player._useAnyResourceFromTopCardDecider = GetRandomDecider(GetAnyResourceFromTopCardInputsCount, AdditionalNeuronsCount, 2);
player._resourceFromTopCardDecider = GetRandomDecider(GetResourceFromTopCardInputsCount, AdditionalNeuronsCount, 4);
player._resourceFromCharityDecider = GetRandomDecider(GetResourceFromCharityInputsCount, AdditionalNeuronsCount, 6);
player._resourceFromInstrumentsDecider = GetRandomDecider(GetResourceFromInstrumentsInputsCount, AdditionalNeuronsCount, 4);
player._leaveHungryDecider = GetRandomDecider(GetLeaveHungryInputsCount, AdditionalNeuronsCount, 2);
return(player);
}
public static AIGeneticPlayer CreateFromCrossover(AIGeneticPlayer parent1, AIGeneticPlayer parent2)
{
const float MutationRate = 0.005f;
AIGeneticPlayer player = new AIGeneticPlayer();
player._whereToGoDecider = GetDeciderFromCrossover(parent1._whereToGoDecider, parent2._whereToGoDecider, MutationRate, WhereToGoInputsCount, AdditionalNeuronsCount, 16);
player._humansCountDecider = GetDeciderFromCrossover(parent1._humansCountDecider, parent2._humansCountDecider, MutationRate, GetUsedHumansInputsCount, AdditionalNeuronsCount, 9);
player._useAnyResourceFromTopCardDecider = GetDeciderFromCrossover(parent1._useAnyResourceFromTopCardDecider, parent2._useAnyResourceFromTopCardDecider, MutationRate, GetAnyResourceFromTopCardInputsCount, AdditionalNeuronsCount, 2);
player._resourceFromTopCardDecider = GetDeciderFromCrossover(parent1._resourceFromTopCardDecider, parent2._resourceFromTopCardDecider, MutationRate, GetResourceFromTopCardInputsCount, AdditionalNeuronsCount, 4);
player._resourceFromCharityDecider = GetDeciderFromCrossover(parent1._resourceFromCharityDecider, parent2._resourceFromCharityDecider, MutationRate, GetResourceFromCharityInputsCount, AdditionalNeuronsCount, 6);
player._resourceFromInstrumentsDecider = GetDeciderFromCrossover(parent1._resourceFromInstrumentsDecider, parent2._resourceFromInstrumentsDecider, MutationRate, GetResourceFromInstrumentsInputsCount, AdditionalNeuronsCount, 4);
player._leaveHungryDecider = GetDeciderFromCrossover(parent1._leaveHungryDecider, parent2._leaveHungryDecider, MutationRate, GetLeaveHungryInputsCount, AdditionalNeuronsCount, 2);
return(player);
}
private IEnumerator RunningGeneration(int generationsCount)
{
for (int generationInd = 0; generationInd < generationsCount; generationInd++)
{
Thread thread = new Thread(new ThreadStart(() => {
PlayGeneration(_population.Players, GamesPerPlayer, (maxScores, averageScores, model) => {
for (int i = 0; i < _population.Players.Count; i++)
{
_population.Players[i].MaxScore = maxScores[i];
_population.Players[i].AverageScore = averageScores[i];
_bestGamePlayerModel = model;
}
});
}));
thread.Start();
while (thread.IsAlive)
{
yield return(new WaitForEndOfFrame());
}
_population.Generation++;
_population.Players.Sort((player1, player2) => {
return(player1.AverageScore.CompareTo(player2.AverageScore));
});
// Remove worst genes.
int DeathCount = Mathf.RoundToInt(DeathRate * _population.Players.Count);
for (int i = 0; i < DeathCount; i++)
{
_population.Players.RemoveAt(0);
}
// Add best genes.
int ReproductiveCount = Mathf.RoundToInt(ReproductivePercent * _population.Players.Count);
for (int i = 0; i < DeathCount; i++)
{
int parent1Ind = _population.Players.Count - UnityEngine.Random.Range(0, ReproductiveCount) - 1;
int parent2Ind = _population.Players.Count - UnityEngine.Random.Range(0, ReproductiveCount) - 1;
AIGeneticPlayer child = AIGeneticPlayer.CreateFromCrossover(_population.Players[parent1Ind].Player, _population.Players[parent2Ind].Player);
PopulationItem childItem = new PopulationItem();
childItem.Player = child;
_population.Players.Insert(0, childItem);
}
UpdateView();
}
}
void PlayMatch()
{
List <Player> players = new List <Player> ()
{
new HumanPlayer(_view.TurnView),
AIGeneticPlayer.CreateRandom(),
AIGeneticPlayer.CreateRandom(),
new AIRandomPlayer()
};
_game = new Game(players);
_view.Init(_game);
Thread thread = new Thread(new ThreadStart(() => { _game.Play(() => {
Debug.Log("Match ended");
}); }));
thread.Start();
}
