def test_with_all_hypothesis(self):
brave = BraveHypothesis()
wimpy = WimpyHypothesis()
knn3 = KNearestNeighbors(3)
knn5 = KNearestNeighbors(5)
knn7 = KNearestNeighbors(7)
knn11 = KNearestNeighbors(11)
rando = RandoHypothesis()
prob = SimpleProbabilityHypothesis()
# drP3 = OptimusPerceptron(11)
# drP5 = DrPerceptron(5)
# drP7 = DrPerceptron(7)
# drP11 = DrPerceptron(11)
#
self.setUpDecisioner(brave,
wimpy,
knn3,
knn5,
knn7,
knn11,
rando,
prob,
# drP3,
# drP5,
# drP7,
# drP11,
)
def create_monster():
color = randint(1, 100)
if color < 70:
if random() >= 0.3:
return Monster(0, [color], 'passive')
return Monster(1, [color], 'aggressive')
else:
if random() >= 0.7:
return Monster(0, [color], 'passive')
return Monster(1, [color], 'aggressive')
for i in range(100):
monster = create_monster()
self.decisioner.update(monster.color, 1, monster.action(True))
maximum_value = 1000.0
actual_value = 0.0
for i in range(1000):
monster = create_monster()
guess = self.decisioner.get_guess(monster.color)
outcome = monster.action(guess)
self.decisioner.update(monster.color, guess, outcome)
maximum_value -= monster._aggressive
actual_value += outcome
class SimpleProbabilityHypothesisTest(unittest.TestCase):
def setUp(self):
self.hypothesis = SimpleProbabilityHypothesis()
def tearDown(self):
self.hypothesis = None
def test_half_probability(self):
self.run_tests_probability_p(0.99)
def run_tests_probability_p(self, p):
# Train inital period
for i in range(100):
monster = create_monster(p)
self.hypothesis.update(monster.color, 1, monster.action(True))
for x in range(500):
monster = create_monster(p)
guess = self.hypothesis.get_guess(monster.color)
outcome = monster.action(guess)
self.hypothesis.update(monster.color, guess, outcome)
err = abs(self.hypothesis.p_value() - p)
self.assertGreater(0.05, err)
class SimpleProbabilityHypothesisTest(unittest.TestCase):
def setUp(self):
self.hypothesis = SimpleProbabilityHypothesis()
def tearDown(self):
self.hypothesis = None
def test_half_probability(self):
self.run_tests_probability_p(0.99)
def run_tests_probability_p(self, p):
# Train inital period
for i in range(100):
monster = create_monster(p)
self.hypothesis.update(monster.color, 1, monster.action(True))
for x in range(500):
monster = create_monster(p)
guess = self.hypothesis.get_guess(monster.color)
outcome = monster.action(guess)
self.hypothesis.update(monster.color, guess, outcome)
err = abs(self.hypothesis.p_value() - p)
self.assertGreater(0.05, err)
def setUp(self):
self.hypothesis = SimpleProbabilityHypothesis()
hyps = [
BraveHypothesis(),
WimpyHypothesis(),
KNearestNeighbors(3),
KNearestNeighbors(5),
KNearestNeighbors(7),
KNearestNeighbors(11),
KNearestNeighbors(17),
KNearestNeighbors(23),
KNearestNeighbors(29),
KNearestNeighbors(31),
KNearestNeighbors(37),
KNearestNeighbors(41),
KNearestNeighbors(43),
KNearestNeighbors(47),
SimpleProbabilityHypothesis(),
RandoHypothesis(),
OptimusPerceptron(47), # mod 47 universe
OptimusPerceptron(43), # mod 43 universe
OptimusPerceptron(41), # mod 41 universe
OptimusPerceptron(37), # mod 37 universe
OptimusPerceptron(31), # mod 31 universe
OptimusPerceptron(29), # mod 29 universe
OptimusPerceptron(23), # mod 23 universe
OptimusPerceptron(17), # mod 17 universe
OptimusPerceptron(11), # mod 11 universe
OptimusPerceptron(7), # mod 7 universe
OptimusPerceptron(5), # mod 5 universe
OptimusPerceptron(3), # mod 3 universe
OptimusPerceptron(2), # even universe
OptimusPerceptron(
def setUp(self):
self.hypothesis = SimpleProbabilityHypothesis()
