def test_strategy(self):
"""Tests that it chooses the best strategy."""
random.seed(9)
p1 = axelrod.ArrogantQLearner()
p1.state = 'CCDC'
p1.Qs = {'': {C: 0, D: 0}, 'CCDC': {C: 2, D: 6}}
p2 = axelrod.Cooperator()
test_responses(self, p1, p2, [], [], [C, C, C, C, C, C, C])
def test_prev_state_updates(self):
"""Test that the q and v values update."""
random.seed(5)
p1 = axelrod.ArrogantQLearner()
p2 = axelrod.Cooperator()
simulate_play(p1, p2)
self.assertEqual(p1.prev_state, '0.0')
simulate_play(p1, p2)
self.assertEqual(p1.prev_state, 'C1.0')
def test_vs_update(self):
"""Test that the q and v values update."""
random.seed(5)
p1 = axelrod.ArrogantQLearner()
p2 = axelrod.Cooperator()
simulate_play(p1, p2)
self.assertEqual(p1.Vs, {'': 0.9, '0.0': 0})
simulate_play(p1, p2)
self.assertEqual(p1.Vs, {'': 0.9, '0.0': 2.7, 'C1.0': 0})
def test_reset_method(self):
"""Tests the reset method."""
P1 = axelrod.ArrogantQLearner()
P1.Qs = {'': {C: 0, D: -0.9}, '0.0': {C: 0, D: 0}}
P1.Vs = {'': 0, '0.0': 0}
P1.history = [C, D, D, D]
P1.prev_state = C
P1.reset()
self.assertEqual(P1.prev_state, '')
self.assertEqual(P1.Vs, {'': 0})
self.assertEqual(P1.Qs, {'': {C: 0, D: 0}})
def test_reset_method(self):
"""Tests the reset method."""
P1 = axelrod.ArrogantQLearner()
P1.Qs = {'': {'C': 0, 'D': -0.9}, '0.0': {'C': 0, 'D': 0}}
P1.Vs = {'': 0, '0.0': 0}
P1.history = ['C', 'D', 'D', 'D']
P1.prev_state = 'C'
P1.reset()
self.assertEqual(P1.prev_state, '')
self.assertEqual(P1.history, [])
self.assertEqual(P1.Vs, {'': 0})
self.assertEqual(P1.Qs, {'': {'C': 0, 'D': 0}})
def test_strategy(self):
"""Tests that it chooses the best strategy."""
random.seed(9)
p1 = axelrod.ArrogantQLearner()
p1.state = 'CCDC'
p1.Qs = {'': {'C': 0, 'D': 0}, 'CCDC': {'C': 2, 'D': 6}}
p2 = axelrod.Cooperator()
self.assertEqual(p1.strategy(p2), 'C')
self.assertEqual(p1.strategy(p2), 'D')
self.assertEqual(p1.strategy(p2), 'D')
self.assertEqual(p1.strategy(p2), 'D')
self.assertEqual(p1.strategy(p2), 'D')
self.assertEqual(p1.strategy(p2), 'D')
def test_prev_state_updates(self):
"""
Test that the q and v values update
"""
random.seed(5)
p1 = axelrod.ArrogantQLearner()
p2 = axelrod.Cooperator()
play_1, play_2 = p1.strategy(p2), p2.strategy(p1)
p1.history.append(play_1)
p2.history.append(play_2)
self.assertEqual(p1.prev_state, '0.0')
play_1, play_2 = p1.strategy(p2), p2.strategy(p1)
p1.history.append(play_1)
p2.history.append(play_2)
self.assertEqual(p1.prev_state, 'C1.0')
def test_qs_update(self):
"""Test that the q and v values update."""
random.seed(5)
p1 = axelrod.ArrogantQLearner()
p2 = axelrod.Cooperator()
play_1, play_2 = simulate_play(p1, p2)
self.assertEqual(p1.Qs, {'': {C: 0, D: 0.9}, '0.0': {C: 0, D: 0}})
simulate_play(p1, p2)
self.assertEqual(p1.Qs, {
'': {
C: 0,
D: 0.9
},
'0.0': {
C: 2.7,
D: 0
},
'C1.0': {
C: 0,
D: 0
}
})
def test_qs_update(self):
"""
Test that the q and v values update
"""
random.seed(5)
p1 = axelrod.ArrogantQLearner()
p2 = axelrod.Cooperator()
play_1, play_2 = p1.strategy(p2), p2.strategy(p1)
p1.history.append(play_1)
p2.history.append(play_2)
self.assertEqual(p1.Qs, {
'': {
'C': 0,
'D': -0.9
},
'0.0': {
'C': 0,
'D': 0
}
})
play_1, play_2 = p1.strategy(p2), p2.strategy(p1)
p1.history.append(play_1)
p2.history.append(play_2)
self.assertEqual(
p1.Qs, {
'': {
'C': 0,
'D': -0.9
},
'0.0': {
'C': 0.9,
'D': 0
},
'C1.0': {
'C': 0,
'D': 0
}
})
def test_stochastic(self):
self.assertTrue(axelrod.ArrogantQLearner().stochastic)
def test_representation(self):
"""
Tests string representation of class
"""
P1 = axelrod.ArrogantQLearner()
self.assertEqual(str(P1), 'Arrogant QLearner')
(axl.Cooperator(), axl.PSOGambler2_2_2()),
(axl.Alternator(), axl.Random()),
(axl.Alternator(), axl.ZDExtort2()),
(axl.Alternator(), axl.GTFT()),
(axl.Alternator(), axl.ALLCorALLD()),
(axl.Alternator(), axl.PSOGambler2_2_2()),
(axl.ALLCorALLD(), axl.Cooperator()),
(axl.ALLCorALLD(), axl.Defector()),
(axl.ALLCorALLD(), axl.TitForTat()),
(axl.Alternator(), axl.Cooperator()),
(axl.Alternator(), axl.Defector()),
(axl.Alternator(), axl.TitForTat()),
(axl.Alternator(), axl.WinStayLoseShift()),
(axl.Defector(), axl.WinStayLoseShift()),
(axl.Calculator(), axl.ALLCorALLD()),
(axl.Calculator(), axl.ArrogantQLearner()),
(axl.Calculator(), axl.Random()),
(axl.Cooperator(), axl.TitForTat()),
(axl.Defector(), axl.Cooperator()),
(axl.Defector(), axl.TitForTat()),
(axl.Random(), axl.Cooperator()),
(axl.Random(), axl.Defector()),
(axl.Random(), axl.TitForTat()),
(axl.WinStayLoseShift(), axl.TitForTat())]
max_N = 20
repetitions = 1000
df = pd.read_csv(
outcomes_file,
header=None,
