def __init__(self, num=0):
self._playernum = num
self._finalboard = fbc.FinalBoardComponent()
self._penalty = p.Penalty()
self._prepboard = pbc.PrepBoardComponent(self._finalboard,
self._penalty)
self._score = 0
self._firstplayer = False
self._projfinalboard = fbc.FinalBoardComponent()
def __init__(self, chromosome, resEval, penEval, fitnessEval, pop):
self.Chromosome = chromosome
self.ResEval = resEval
self.PenEval = penEval
self.FitnessEval = fitnessEval
self.PopulationSize = 400
self.Elitism = 2
self.SelectionOp = TournamentSelectionOperator(2, 2)
self.RecombinationOp = DrunkRecombinationOperator()
self.MutationOp = None
self.PenEval.Evaluate(pop)
self.FitnessEval.Evaluate(pop)
pop.SortByFitness()
self.Population = pop
rdb = Surrogate.ResponseDatabaseFromPopulation(self.Population)
sdb = Surrogate.SuccessDatabaseFromPopulation(self.Population)
self.ResponseModel = Surrogate.RBFNetwork()
self.ResponseModel.Train(rdb)
self.SuccessModel = Surrogate.RBFNetwork()
self.SuccessModel.Train(sdb)
self.SurrogateResEval = SurrogateResponseEvaluator(
self.ResponseModel, self.SuccessModel, self.Chromosome)
self.SurrogateChromosome = self.Chromosome.Clone()
self.SurrogateChromosome.Responses.append(
Value("TorczonMerit", "FLOAT", 0.0))
self.SurrogatePenEval = copy.deepcopy(self.PenEval)
self.SurrogatePenEval.ObjectivePenalties.append(
Penalty("MAXIMIZE", "TorczonMerit", exponent=1.0))
# self.SurrogatePenEval.ConstraintPenalties.append(Penalty("LOWER_BOUND", "__SUCCESS__", 100.0, 1.0, 0.5))
self.TrustRegion = TrustRegion(self.SurrogateChromosome)
self.TrustRegionSize = 1.0
self.TrustRegionCoeffWhenImproved = 1.3 # 1.2
self.TrustRegionCoeffWhenNotImproved = 0.9 # 0.7
self.TrustRegionSizeMinimum = 0.05
self.MeritWeight = 0.01
self.HistoryOutput = open("history.dat", "w")
