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add freqAnalyzer strat
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‎axelrod/strategies/_strategies.py‎

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)
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from .shortmem import ShortMem
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from .stalker import Stalker
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from .frequency_analyzer import FreqAnalyzer
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from .titfortat import (
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AdaptiveTitForTat,
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Alexei,
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AntiTitForTat,
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Bully,
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BurnBothEnds,
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SofteningTitForTat,
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HardeningTitForTat,
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ContriteTitForTat,
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DynamicTwoTitsForTat,
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EugineNier,
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ForgivingTitForTat,
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Fortress3,
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Fortress4,
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FreqAnalyzer,
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GTFT,
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GeneralSoftGrudger,
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GoByMajority,
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Hopeless,
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Inverse,
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InversePunisher,
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SofteningTitForTat,
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HardeningTitForTat,
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KnowledgeableWorseAndWorse,
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LevelPunisher,
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LimitedRetaliate,

‎axelrod/strategies/frequency_analyzer.py‎

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from axelrod.action import Action, actions_to_str
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from axelrod.player import Player
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from axelrod.strategy_transformers import (
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FinalTransformer,
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TrackHistoryTransformer,
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)
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C, D = Action.C, Action.D
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class FreqAnalyzer(Player):
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"""
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A player starts by playing TitForTat for the first 30 turns (dataset generation phase).
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Take the matrix of last 2 moves by both Player and Opponent.
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While in dataset generation phase, construct a dictionary d, where keys are each 4 move sequence
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and the corresponding value for each key is a list of the subsequent Opponent move. The 4 move sequence
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starts with the Opponent move.
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For example, if a game at turn 5 looks like this:
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Opp: C, C, D, C, D
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Player: C, C, C, D, C
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d should look like this:
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{ [CCCC]: [D],
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[CCDC]: [C],
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[DCCD]: [D] }
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During dataset generation phase, Player will play TitForTat. After end of dataset generation phase,
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Player will switch strategies. Upon encountering a particular 4-move sequence in the game, Player will look up history
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of subsequent Opponent move. If ratio of defections to total moves exceeds p, Player will defect. Otherwise,
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Player will cooperate.
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Could fall under "Hunter" class of strategies.
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More likely falls under LookerUp class of strategies.
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Names:
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- FreqAnalyzer (FREQ): Original by Ian Miller
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"""
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# These are various properties for the strategy
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name = "FreqAnalyzer"
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classifier = {
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"memory_depth": float("inf"),
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"stochastic": False,
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"long_run_time": False,
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"inspects_source": False,
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"manipulates_source": False,
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"manipulates_state": False,
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}
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def __init__(self) -> None:
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"""
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Parameters
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----------
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p, float
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The probability to cooperate
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"""
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super().__init__()
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self.minimum_cooperation_ratio = 0.5
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self.frequency_table = dict()
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self.last_sequence = ''
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self.current_sequence = ''
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def strategy(self, opponent: Player) -> Action:
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"""This is the actual strategy"""
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if len(self.history) > 5:
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self.last_sequence = str(opponent.history[-3]) + str(self.history[-3]) + str(opponent.history[-2]) + str(self.history[-2])
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self.current_sequence = str(opponent.history[-2]) + str(self.history[-2]) + str(opponent.history[-1]) + str(self.history[-1])
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self.update_table(opponent)
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if len(self.history) < 30:
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# Play TitForTat
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# First move
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if not self.history:
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return C
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# React to the opponent's last move
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if opponent.history[-1] == D:
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return D
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return C
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else:
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try:
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results = self.frequency_table[self.current_sequence]
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cooperates = results.count('C')
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if (cooperates / len(self.history)) > self.minimum_cooperation_ratio:
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return C
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return D
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except:
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if not self.history:
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return C
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# React to the opponent's last move
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if opponent.history[-1] == D:
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return D
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return C
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def update_table(self, opponent: Player):
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print(self.frequency_table)
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print("___________________")
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print("current sequence is {}", self.last_sequence)
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if self.last_sequence in self.frequency_table.keys():
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print("seen this key before")
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print("freq table keys = {}", self.frequency_table.keys())
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results = self.frequency_table[self.last_sequence]
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results.append(opponent.history[-1])
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self.frequency_table[self.last_sequence] = results
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else:
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print("not seen this key ever")
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self.frequency_table[self.last_sequence] = [opponent.history[-1]]
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‎axelrod/tests/strategies/test_freqanalyzer.py‎

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"""Tests for the Stalker strategy."""
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import axelrod as axl
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from .test_player import TestPlayer
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C, D = axl.Action.C, axl.Action.D
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class TestStalker(TestPlayer):
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name = "Stalker: (D,)"
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player = axl.Stalker
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expected_classifier = {
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"memory_depth": float("inf"),
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"stochastic": True,
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"makes_use_of": {"game", "length"},
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"long_run_time": False,
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"inspects_source": False,
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"manipulates_source": False,
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"manipulates_state": False,
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}
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def test_strategy(self):
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actions = [(C, C)] * 3 + [(D, C)]
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self.versus_test(opponent=axl.Cooperator(), expected_actions=actions)
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# wish_score < current_average_score < very_good_score
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actions = [(C, C)] * 7 + [(C, D), (C, D), (C, C), (C, C), (D, C)]
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self.versus_test(
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opponent=axl.MockPlayer(actions=[C] * 7 + [D] * 2),
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expected_actions=actions,
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)
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actions = [(C, C)] * 7 + [(C, D), (C, C), (D, C)]
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self.versus_test(
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opponent=axl.MockPlayer(actions=[C] * 7 + [D]),
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expected_actions=actions,
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)
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# current_average_score > 2
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actions = [(C, C)] * 9 + [(D, C)]
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self.versus_test(axl.Cooperator(), expected_actions=actions)
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# 1 < current_average_score < 2
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actions = [(C, C)] * 7 + [(C, D)] * 4 + [(D, D)]
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self.versus_test(
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opponent=axl.MockPlayer(actions=[C] * 7 + [D] * 5),
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expected_actions=actions,
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)
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def test_strategy2(self):
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# current_average_score < 1
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actions = (
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[(C, D)]
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+ [(D, D)] * 2
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+ [(C, D)] * 3
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+ [(D, D), (C, D), (D, D), (C, D), (D, D), (C, D), (D, D)]
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)
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self.versus_test(axl.Defector(), expected_actions=actions, seed=3222)
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def test_strategy3(self):
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actions = [(C, D)] * 3 + [
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(D, D),
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(C, D),
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(D, D),
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(C, D),
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(C, D),
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(D, D),
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(C, D),
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(C, D),
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(C, D),
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(D, D),
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]
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self.versus_test(axl.Defector(), expected_actions=actions, seed=649)
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def test_strategy4(self):
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# defect in last round
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actions = [(C, C)] * 199 + [(D, C)]
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self.versus_test(
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axl.Cooperator(),
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expected_actions=actions,
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match_attributes={"length": 200},
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)
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# Force a defection before the end of the actual match which ensures
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# that current_average_score > very_good_score
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actions = [(C, C)] * 3 + [(D, C)] * 3
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self.versus_test(
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opponent=axl.Cooperator(),
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expected_actions=actions,
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match_attributes={"length": 4},
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)

‎run_mypy.py‎

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"axelrod/strategies/darwin.py",
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"axelrod/strategies/defector.py",
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"axelrod/strategies/forgiver.py",
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"axelrod/strategies/frequency_analyzer.py",
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"axelrod/strategies/gradualkiller.py",
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"axelrod/strategies/grudger.py",
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"axelrod/strategies/grumpy.py",

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