private static double Fitness(IPhenotype p)
{
var phenotype = (CollectivePhenotype <ParabolicParameters>)p;
var x = phenotype.GetValue();
var distributions = GenerateDistributions(x, DistributionResolution).ToArray();
var differences = new Distribution[2];
for (var i = 0; i < differences.Length; i++)
{
differences[i] = distributions[i] - TestedDistributions[i];
}
var average = differences.Select(d => d.Average()).ToArray();
var standardDeviation = differences.Select((d, index) => d.StandardDeviation(average[index])).ToArray();
var fitness = new double[differences.Length];
for (var i = 0; i < differences.Length; i++)
{
fitness[i] = Math.Abs(average[i]) + Math.Abs(standardDeviation[i]);
}
return(fitness.Max());
}
public static double Fitness(IPhenotype p)
{
var phenotype = (CollectivePhenotype <EllipticParameters>)p;
var x = phenotype.GetValue();
var ellipsis = new Ellipsis(x, AnalyzedPointSet.Center.Z);
if (ellipsis.Eccentricity > EccentricityThreshold)
{
return(double.MaxValue);
}
double fitness = 0;
var counter = 0;
double maxDistance = 0;
var offsetFoci1 = x.F1 + AnalyzedPointSet.Center;
var offsetFoci2 = x.F2 + AnalyzedPointSet.Center;
foreach (var point in AnalyzedPointSet)
{
// Distance of point from Foci 1
var pf1 = MathUtils.Distance(point, offsetFoci1, MathUtils.EDistanceMetric.Euclidean, MathUtils.EDimension.X,
MathUtils.EDimension.Y);
// Distance of point from Foci 2
var pf2 = MathUtils.Distance(point, offsetFoci2, MathUtils.EDistanceMetric.Euclidean, MathUtils.EDimension.X,
MathUtils.EDimension.Y);
// Given two fixed points F1 and F2 called the foci, and a distance 2a, which is greater than the distance between the foci,
// the ellipse is the set of points P such that the sum of the distances PF1, PF2 is equal to 2a:
var dist = pf1 + pf2 - 2 * x.A;
if (double.IsNaN(dist))
{
return(double.MaxValue);
}
var absoluteDistance = Math.Abs(dist);
if (absoluteDistance > BufferWidth)
{
fitness += absoluteDistance;
counter++;
}
if (absoluteDistance > maxDistance)
{
maxDistance = absoluteDistance;
}
}
fitness /= counter;
fitness += maxDistance;
fitness /= 2;
return(fitness);
}
public Individual(IGenotype genotype, IPhenotype phenotype)
{
Genotype = genotype;
Phenotype = phenotype;
Phenotype.Genotype = genotype;
if (_fitnessFunction != null)
{
return;
}
var factory = new TFitnessFunctionFactory();
_fitnessFunction = factory.Make();
}
public BehaviorPhenotypeEntity(RobotEvolutionConfiguration config, int entityIndex)
{
Phenotypes = new IPhenotype[]
{
new Phenotype("LookAheadCycles", LookAheadCyclesBits)
{
MinValue = 0,
MaxValue = 254
},
new Phenotype("BehaviorWeight", BehaviorWeightBits)
{
MinValue = 0,
MaxValue = 10
}
};
}
private double GetValue(IEnumerable <int> genes, int skip, IPhenotype phenotype)
{
var representation = string.Join(String.Empty, genes.Skip(skip).Take(phenotype.Length));
var value = (float)BinaryStringRepresentation.ToDouble(representation, 0);
if (value < phenotype.MinValue)
{
return(phenotype.MinValue);
}
if (value > phenotype.MaxValue)
{
return(phenotype.MaxValue);
}
return(value);
}
public BrickPhenotypeEntity(Vector3 minPosition, Vector3 maxPosition)
{
Phenotypes = new IPhenotype[]
{
new Phenotype("x", 5)
{
MinValue = minPosition.x, MaxValue = maxPosition.x
},
new Phenotype("y", 5)
{
MinValue = minPosition.y, MaxValue = maxPosition.y
},
new Phenotype("z", 5)
{
MinValue = minPosition.z, MaxValue = maxPosition.z
},
};
}
public CarVectorPhenotypeEntity(CarSampleConfig config, int entityIndex)
{
Phenotypes = new IPhenotype[]
{
new Phenotype("VectorSize", VectorSizeBits)
{
MinValue = 1,
MaxValue = config.MaxVectorSize
},
new Phenotype("VectorAngle", VectorAngleBits)
{
MinValue = 0,
MaxValue = 359
},
new CarWheelIndexPhenotype(config, entityIndex),
new CarWheelRadiusPhenotype(config, entityIndex)
};
}
public ShootVectorPhenotypeEntity(ShooterSampleConfig config, int entityIndex)
{
Phenotypes = new IPhenotype[]
{
new Phenotype("Vector_Y_Shoot", Shoot_Y_VectorBits_Bits)
{
MinValue = 0,
MaxValue = config.Max_VectorAngle
},
new Phenotype("Vector_Z_Shoot", Shoot_Z_VectorBits_Bits)
{
MinValue = 0,
MaxValue = config.Max_VectorAngle
},
new Phenotype("Vector_Strengh", Shoot_VectorStrengh_Bits)
{
MinValue = 0,
MaxValue = config.MaxStrengh
}
};
}
public int CompareTo(IPhenotype other)
{
return(Fitness.CompareTo(other.Fitness));
}
public double GetValue(IPhenotype x)
{
return(Function(x));
}
