public void Cycle()
{
if (OldGeneration.Count > 0)
{
for (int i = 0; i < OldGeneration.Count; i++)
{
SetNeighbours(OldGeneration[i]);
}
OldGeneration.AddRange(_neighbours);
_neighbours.Clear();
foreach (var cell in OldGeneration)
{
Cell newCell = Rules.Apply(cell);
_cellService.DrawCell(newCell);
if (newCell.State == State.ALive)
{
newCell.Neighbours = 0;
NewGeneration.Add(newCell);
}
}
OldGeneration = new List <Cell>(NewGeneration);
NewGeneration.Clear();
}
}
/// <summary>
/// Prepares the next round of generation
/// <para/> - Picks the winners
/// <para/> - Reproduces new children
/// <para/> - Generates new AIs if needed
/// <para/> - Resets the AIs
/// </summary>
private void newRound()
{
Round++;
//Pick the ais to keep based on their score, and tie-breaked by their match results
lastWinners = ais
.OrderByDescending(ai => ai.NetScore)
.ThenByDescending(ai => ai.NetMatches)
.Take((int)gc.KeepBestAIs)
.Select(ai => ai.Brain)
.ToArray();
//Update stats
CurrBestScore = ais.OrderByDescending(ai => ai.NetScore).First().NetScore;
AverageScore = (int)ais.Average(ai => ai.NetScore);
if (CurrBestScore > BestScore || BestScoreRound == 0)
{
BestScoreRound = Round;
BestScore = CurrBestScore;
}
//Set the first AIs as the kept winners
for (int i = 0; i < lastWinners.Length && i < ais.Length; i++)
{
ais[i].Brain = lastWinners[i];
}
//Generates children for the kept AIs
int currIndex;
for (currIndex = lastWinners.Length; currIndex < ais.Length && currIndex < gc.MaximumChildrenPerAi * gc.KeepBestAIs; currIndex++)
{
const int slowDownFactor = 100;
float currEvolutionFactor = ((gc.BaseEvolutionFactor / 100.0f) * slowDownFactor) / (slowDownFactor + Round);
ais[currIndex].Brain = lastWinners[currIndex % lastWinners.Length].GenerateChild(currEvolutionFactor);
}
//If we don't have enough AIs, generate new random ones
for (int i = currIndex; i < ais.Length; i++)
{
ais[i].Brain = new Brain(gc.NeuronCount, gc.LayerCount, gc.MemoryNeuronCount);
}
//Reset scores
foreach (AiPlayed ai in ais)
{
ai.NetScore = 0;
ai.NetMatches = 0;
for (int i = 0; i < ai.GamesPlayed.Length; i++)
{
ai.GamesPlayed[i] = false;
}
}
doneCount = 0;
NewGeneration?.Invoke();
}
public static void Main()
{
StarTrek baseClass = new StarTrek();
NewGeneration childClass = new NewGeneration();
baseClass.ShowEnum();
childClass.ShowEnum();
Console.ReadLine();
}
private void Start()
{
// Get references to all of the individuals in the simulation
population = GetComponentsInChildren <Individual>();
nextGeneration = GetComponentsInChildren <Individual>();
// Initialize utility classes
evaluator = new FitnessEvaluator(target);
evaluator.ComputeMaxFitness();
nextGen = new NewGeneration(copier);
}
protected virtual void OnNewGeneration(GenerationResult <T, TScore> e)
{
NewGeneration?.Invoke(this, e);
}
static private void OnNewGeneration(object sender, EventArgs e)
{
NewGeneration?.Invoke(sender, e);
}
public void SetInitialState()
{
OldGeneration.Clear();
NewGeneration.Clear();
_neighbours.Clear();
}
