public void Init(SnakeRunnerSmart snakeRunner, IGenomeDecoder <NeatGenome, IBlackBox> genomeDecoder)
{
_snakeRunner = snakeRunner;
_sw = _snakeRunner.SnakeWorld;
_genomeDecoder = genomeDecoder;
this.Size = new Size((_sw.Width + 2) * _scaleFactor, (_sw.Height + 6) * _scaleFactor);
}
public FitnessInfo Evaluate(IBlackBox phenome)
{
SimpleSnakeWorld sw = new SimpleSnakeWorld(_swparams);
sw.Init();
SnakeRunnerSmart sr = new SnakeRunnerSmart(sw, phenome, _inputMapper, _outputMapper, 0, _maxTicksWithoutEating);
//SimpleSnakeWorld clone = _srf.GetWorldClone();
//clone.Init();
//SnakeRunner sr = new SnakeRunnerWxH(clone, phenome, 0, _maxTicksWithoutScoreChange);
int totalSquaredScore = 0;
int totalScore = 0;
int totalTicks = 0;
double inverseOfMediumFoodDistance = 0;
_wins = 0;
int cutoffs = 0;
for (int runs = 0; runs < _trialsPerEvaluation; runs++)
{
sr.RunTrial(runs);
totalSquaredScore += sr.Score * sr.Score; //was totalScore += sr.Score; changed to emphasize large scores over lower scores
totalScore += sr.Score;
totalTicks += sr.Ticks;
//inverseOfMediumFoodDistance += sr.Score / (double) sr.TotalFoodDistance;
if (sr.Win)
{
_wins++;
}
//if (sr.Cutoff)
// cutoffs++;
}
EvaluationCount++;
return(new FitnessInfo(totalScore, totalSquaredScore)); //probably a good one
//return new FitnessInfo(totalSquaredScore, totalScore);
//return new FitnessInfo(totalScore, Double.MaxValue/(totalSquaredScore+1));
//return new FitnessInfo(totalScore, Double.MaxValue / (totalSquaredScore - totalScore + 1)); //probably a good one
//TODO: magari cambiare la fitness...
//return new FitnessInfo((double)(totalSquaredScore + totalScore*totalScore)/1024, totalScore);
//return new FitnessInfo(phenome.GetHashCode(), phenome.GetHashCode()); //prova
}
