Jodoyle29 patch 1

axelrod/strategies/_strategies.py

@@ -205,6 +205,7 @@
 from .mutual import Desperate, Hopeless, Willing
 from .negation import Negation
 from .oncebitten import FoolMeOnce, ForgetfulFoolMeOnce, OnceBitten
+from .probabilistic_hill_climb import ProbabilisticHillClimb
 from .prober import (
     CollectiveStrategy,
     Detective,
@@ -423,6 +424,7 @@
     PSOGamblerMem1,
     Pi,
     Predator,
+    ProbabilisticHillClimb,
     Prober,
     Prober2,
     Prober3,

axelrod/strategies/probabilistic_hill_climb.py

@@ -0,0 +1,55 @@
+from axelrod.action import Action
+from axelrod.player import Player
+
+C, D = Action.C, Action.D
+
+class ProbabilisticHillClimb(Player):
+	"""
+	Defects with probability of 50%.
+	Every time the oppenent deffects, probability becomes '(100 + 1)/100', increasing by 1%.
+	Every time the opponent confesses, probability becomes '(100 - 1)/100', decreasing by 1%.
+	In case of error (conditions aren't triggered, repeat last move)
+
+	This strategy is based on the following assumption: if the opponent is going to deffect,
+	it is better to deffect. If the opponent is going to confess, it is better to confess. 
+	Using a simple probabilistic approach, we can predict the opponents nexzt move and chose
+	to confess/deffect accordingly.
+
+	"""
+
+	name = "Hill Climb"
+	classifier = {
+		"memory_depth": float("inf"),
+		"stochastic": True,
+		"long_run_time": False,
+		"inpects_source": False,
+		"manipulates_source": False,
+		"manipulates_state": False,
+	}
+
+	def __init__(self) -> None:
+		super().__init__()
+		self.probability = 0.5
+
+	def strategy(self, opponent: Player) -> Action:
+		"""Actual strategy definition that determines player's action."""
+		MAX = 100
+		if not len(opponent.history): # if opponent has no previous moves, confess on first move
+			return C
+
+		else:
+			if opponent.history[-1] == D:
+				self.probability += 1/MAX
+				if(self.probability >= 1):
+					self.probability = 0.5 # to excape local maxima
+				return self._random.random_choice(self.probability)
+
+			if opponent.history[-1] == C:
+				self.probability -= 1/MAX
+				if(self.probability <= 0):
+					self.probability = 0.1 # avoid crash
+				return self._random.random_choice(self.probability)
+
+			else:
+				print("There has been an error")
+				return self.history[-1]

docs/reference/strategy_index.rst

@@ -82,6 +82,8 @@ Here are the docstrings of all the strategies in the library.
    :members:
 .. automodule:: axelrod.strategies.oncebitten
    :members:
+.. automodule:: axelrod.strategies.probabilistic_hill_climb
+   :members:
 .. automodule:: axelrod.strategies.prober
    :members:
 .. automodule:: axelrod.strategies.punisher