/// <summary>
/// Generates the next boardstate or returns false if unable
/// </summary>
private Board generate(ExactChromosome max, Board b)
{
MovesTaken++;
Debug.Assert(b.Turn % 2 == 0);
int i = b.Turn / 2;
if (max.moves.Count <= i)
{
max.moves.Add(null);
}
if (max.moves[i] == null || !max.moves[i].isLegal(b))
{
illegals++;
max.moves[i] = getExactMove(b);
if (max.moves[i] == null)
{
return null;
}
}
max.boardState[i] = hash(b);
return b.generate(max.moves[i]);
}
public override void takeTurn()
{
RecordHistory.current.record();
AForge.Genetic.Population ga = new AForge.Genetic.Population(popSize, new ExactChromosome(depth), fit, new AForge.Genetic.RankSelection(), random);
bool tempRecord = GameController.recording;
GameController.recording = false;
int i = 0;
while (fit.timesEvaluated < evaluations)
{
//Getting an index out of range exception here when using RouletteWheelSelection (16 rounds in, seed 100)
ga.RunEpoch();
RecordHistory.current.plot(i + "," + ga.FitnessMax + Environment.NewLine);
if ((GameController.turn % 5 == 0) && (i == 0 || i == generations / 2 || i == generations - 1))
{
List<double> fitnesses = ga.getFitnesses();
List<double> parents = ga.getParentFitnesses();
List<string> snap = new List<string>();
for (int j = 0; j < fitnesses.Count; j++) snap.Add(fitnesses[j].ToString() + "," + parents[j].ToString());
RecordHistory.current.snapshot(snap);
}
i++;
}
lastBestChromosome = ga.BestChromosome as ExactChromosome;
fit.timesEvaluated = 0;
GameController.recording = tempRecord;
fit.Evaluate(lastBestChromosome);
Move m = lastBestChromosome.moves[0];
if (m == null)
{
m = Move.getRandomMove();
throw new NullReferenceException("ExactGene couldn't find a random move.");
}
CONSOLE.Overwrite(12, "Illegals: " + fit.Illegals);
CONSOLE.Overwrite(13, "Moves: " + fit.MovesTaken);
takeAction(m);
RecordHistory.current.record(this + " took move " + m);
}
/// <summary>
/// Evaluates a chromosome against Greedy
/// </summary>
private double score(ExactChromosome max)
{
Board current = Board.current;
Board next;
Move nextMove;
Move pred = null; //Predicted move next turn for Greedy
double score = 0;
int i = 0;
while (current.Turn < depth)
{
if (predictWin(current, pred)) break;
next = generate(max, current);
if (next == null) break;
score += scoringFunction.evaluate(next);
i++;
current = next;
if (predictWin(current, pred)) break;
//Do the "Generate-next-move" loop for greedy
nextMove = Greedy.getGreedyMove(current, greedy);
if (i == 1) pred = nextMove;
if (nextMove != null)
{
current = current.generate(nextMove);
}
else
{
break;
}
}
if (max.parentFitness > 0 && score > max.parentFitness)
{
ExactChromosome.crossOverImprovements += 1;
}
else if (max.parentFitness < 0 && score > -max.parentFitness)
{
ExactChromosome.mutationImprovements += 1;
}
return score / i;
}
