import math
from axelrod.action import Action
from axelrod.player import Player
C, D = Action.C, Action.D
[docs]class CotoDeRatio(Player):
"""The player will always aim to bring the ratio of co-operations to
defections closer to the ratio as given in a sub class
Names:
- Co to Do Ratio: Original Name by Timothy Standen
"""
classifier = {
"stochastic": False,
"memory_depth": float("inf"), # Long memory
"long_run_time": False,
"inspects_source": False,
"manipulates_source": False,
"manipulates_state": False,
}
[docs] def strategy(self, opponent: Player) -> Action:
# Initially cooperate
if len(opponent.history) == 0:
return C
# Avoid initial division by zero
if not opponent.defections:
return D
# Otherwise compare ratio to golden mean
cooperations = opponent.cooperations + self.cooperations
defections = opponent.defections + self.defections
if cooperations / defections > self.ratio:
return D
return C
[docs]class Golden(CotoDeRatio):
"""The player will always aim to bring the ratio of co-operations to
defections closer to the golden mean
Names:
- Golden: Original Name by Timothy Standen
"""
name = "$\phi$"
ratio = (1 + math.sqrt(5)) / 2
[docs]class Pi(CotoDeRatio):
"""The player will always aim to bring the ratio of co-operations to
defections closer to the pi
Names:
- Pi: Original Name by Timothy Standen
"""
name = "$\pi$"
ratio = math.pi
[docs]class e(CotoDeRatio):
"""The player will always aim to bring the ratio of co-operations to
defections closer to the e
Names:
- e: Original Name by Timothy Standen
"""
name = "$e$"
ratio = math.e