def test_find_old_classifier_similar_and_subsumer_subsumer_returned(self):
# given
cfg = acs2.Configuration(
classifier_length=8, number_of_possible_actions=4)
subsumer = acs2.Classifier(
condition='1#######',
action=1,
experience=21,
quality=0.95,
cfg=cfg)
similar = acs2.Classifier(
condition='10######',
action=1,
cfg=cfg)
population = acs2.ClassifiersList(*[similar, subsumer])
cl = acs2.Classifier(
condition='10######',
action=1,
cfg=cfg)
# when
old_cls = ga._find_old_classifier(population, cl, True, cfg.theta_exp)
# then
assert similar == cl
assert subsumer == old_cls
def test_should_not_find_old_classifier(self):
# given
cfg = acs2.Configuration(
classifier_length=4, number_of_possible_actions=2)
cl = acs2.Classifier(cfg=cfg)
population = acs2.ClassifiersList()
# when
old_cl = ga._find_old_classifier(population, cl, True, cfg.theta_exp)
# then
assert old_cl is None
def test_should_find_old_classifier_only_subsumer(self):
# given
cfg = acs2.Configuration(
classifier_length=8, number_of_possible_actions=4)
subsumer1 = acs2.Classifier(
condition='1##0####',
action=3,
effect='##1#####',
quality=0.93,
reward=1.35,
experience=23,
cfg=cfg)
subsumer2 = acs2.Classifier(
condition='#1#0####',
action=3,
effect='##1#####',
quality=0.93,
reward=1.35,
experience=23,
cfg=cfg)
most_general = acs2.Classifier(
condition='###0####',
action=3,
effect='##1#####',
quality=0.93,
reward=1.35,
experience=23,
cfg=cfg)
nonsubsumer = acs2.Classifier(cfg=cfg)
cl = acs2.Classifier(
condition='11#0####',
action=3,
effect='##1#####',
quality=0.5,
reward=0.35,
experience=1,
cfg=cfg)
population = acs2.ClassifiersList(
*[nonsubsumer, subsumer1, nonsubsumer, most_general,
subsumer2, nonsubsumer])
# when
old_cl = ga._find_old_classifier(population, cl, True, cfg.theta_exp)
# then
assert old_cl == most_general
def test_find_old_classifier_only_similar(self):
# given
cfg = acs2.Configuration(
classifier_length=4, number_of_possible_actions=2)
cl_1 = acs2.Classifier(action=1, experience=32, cfg=cfg)
cl_2 = acs2.Classifier(action=1, cfg=cfg)
population = acs2.ClassifiersList(
*[cl_1,
acs2.Classifier(action=2, cfg=cfg),
acs2.Classifier(action=3, cfg=cfg),
cl_2])
# when
cl = acs2.Classifier(action=1, cfg=cfg)
old_cl = ga._find_old_classifier(population, cl, True, cfg.theta_exp)
# then
assert old_cl == cl_1