private void StartNewGeneration()
{
curGeneration++;
finishedBotCount = 0;
generationText.text = "Generation " + curGeneration.ToString();
GeneScore baseGene = null;
List <GeneScore> crossoverCandidates = new List <GeneScore>();
if (geneScores.Count > 0)
{
List <GeneScore> orderedGenes = geneScores.OrderByDescending(x => x.score).ToList();
UpdateLeaderBoard(orderedGenes);
baseGene = new GeneScore(orderedGenes.First().CreateForceGeneCopy());
List <GeneScore> mostFitting = GetMostFitting(orderedGenes.Skip(1).ToList());
foreach (GeneScore gs in mostFitting)
{
crossoverCandidates.Add(new GeneScore(gs.CreateForceGeneCopy()));
}
geneScores = new List <GeneScore>(orderedGenes);
CleanGeneList();
}
for (int i = 0; i < generationTotal; i++)
{
CreateNewBot(i, new Vector3(startPos.x + (i * 4), startPos.y, startPos.z), baseGene, crossoverCandidates);
}
}
private List <ForceGene> GetCrossoverAndMutatedGene(GeneScore baseGene, List <GeneScore> crossoverCandidates)
{
GeneScore newGene = new GeneScore(baseGene.CreateForceGeneCopy());
GeneScore crossoverGene = new GeneScore(newGene.CrossOver(crossoverCandidates));
List <ForceGene> mutatedGene = new GeneScore(crossoverGene.Mutate()).CreateForceGeneCopy();
return(mutatedGene);
}
public void RegisterGene(GeneScore geneScore)
{
finishedBotCount++;
geneScores.Add(geneScore);
if (finishedBotCount == generationTotal)
{
StartNewGeneration();
}
}
private void HandleGenerationComplete(object sender, GenerationCompleteEventArgs args)
{
// Update best if necessary
if (_bestResult == null || args.Scores[0] > _bestResult)
{
_bestResult = args.Scores[0];
}
var iterationsPerSecond = _iterationNumber / (DateTime.Now - _startDateTime).TotalSeconds;
Strategy.Print(Strategy.Instrument.FullName + ": completed generation " + (args.GenerationNumber + 1) + "/" +
__lastParameters.MaximumGenerations + ", iterations per second: " +
iterationsPerSecond.ToString("N1") + ", max fitness this gen: " +
args.Scores[0].Fitness.ToString("N2"));
_parameterWriter.Flush();
}
private void CreateNewBot(int curBotId, Vector3 botPos, GeneScore baseGene, List <GeneScore> crossoverCandidates)
{
GameObject curBot = Instantiate(ragdoll, botPos, Quaternion.identity) as GameObject;
RagdollController ragdollController = curBot.GetComponent <RagdollController>();
ragdollController.Initialize(this, "G" + curGeneration.ToString() + "B" + curBotId.ToString());
if (baseGene == null)
{
ragdollController.StartMoving(GetNewGene(ragdollController.GetNumOfJoints()));
}
else
{
if (curBotId == 0)
{
ragdollController.StartMoving(baseGene.CreateForceGeneCopy());
}
else
{
ragdollController.StartMoving(GetCrossoverAndMutatedGene(baseGene, crossoverCandidates));
}
}
}
public IterationCompleteEventArgs(GeneScore score, int iterationNumber, int iterationsRemaining)
{
_score = score;
_iterationNumber = iterationNumber;
_iterationsRemaining = iterationsRemaining;
}
private void HandleGenerationComplete(object sender, GenerationCompleteEventArgs args)
{
// Update best if necessary
if (_bestResult == null || args.Scores[0] > _bestResult)
{
_bestResult = args.Scores[0];
}
var iterationsPerSecond = _iterationNumber / (DateTime.Now - _startDateTime).TotalSeconds;
Strategy.Print(Strategy.Instrument.FullName + ": completed generation " + (args.GenerationNumber + 1) + "/" +
__lastParameters.MaximumGenerations + ", iterations per second: " +
iterationsPerSecond.ToString("N1") + ", max fitness this gen: " +
args.Scores[0].Fitness.ToString("N2"));
_parameterWriter.Flush();
}
private bool OnIterationComplete(GeneScore score, int iterationCount, int iterationsRemaining)
{
if (IterationComplete != null)
{
var args = new IterationCompleteEventArgs(score, iterationCount, iterationsRemaining);
IterationComplete(this, args);
return args.Stop;
}
return false;
}