def main():
common_classes = CommonClassesCreator(False)
length, epsilon, mutation_neighborhood, tolerance = common_classes.get_common_classes()
concept_class = MonotoneConjunction(length)
performance = common_classes.get_perf_without_precomp(concept_class)
mutation_probability = common_classes.get_mutation_probability()
mutator = Mutator(mutation_neighborhood, performance, tolerance, mutation_probability, epsilon)
algorithm = ConjunctionEvolvabilityAlgorithm(mutator, length, epsilon, performance)
hypo = algorithm.learn_ideal_function(epsilon)
print "HYPO IS: " + str(hypo)
def recombination_main():
common_classes = CommonClassesCreator()
length, epsilon, mutation_neighborhood, tolerance = common_classes.get_common_classes()
mutation_factor = 0.1
concept_class = MonotoneConjunction(length)
performance = common_classes.get_perf_without_precomp(concept_class)
recomb_process = RecombinationProcess()
neighborhood = NeighborhoodWithOtherRepresentations(length, mutation_neighborhood,
mutation_factor, recomb_process)
recombinator = Recombinator(neighborhood, performance, tolerance, epsilon)
recombination = RecombinationConjunctionAlgorithm(recombinator, length, epsilon, concept_class)
recombination.learn_ideal_function(concept_class)
def HGT_main():
common_classes = CommonClassesCreator()
length, epsilon, mutation_neighborhood, tolerance = common_classes.get_common_classes()
mutation_factor = 0.1
HGT_factor = 1
concept_class = MonotoneConjunction(length)
performance = common_classes.get_perf_without_precomp(concept_class)
HGT_process = HGTProcess(HGT_factor, length)
neighborhood = NeighborhoodWithOtherRepresentations(length, mutation_neighborhood,
mutation_factor, HGT_process)
HGT_mutator = HGT_Mutator(neighborhood, performance, tolerance, epsilon, HGT_process)
mutation = HGTConjunctionAlgorithm(HGT_mutator, length, epsilon, performance)
final_population = mutation.learn_ideal_function(concept_class)
if len(final_population) <= 30:
print final_population
