Add new strategy ShortMem (#857)

* Add new strategy ShortMem

* Fix errors

* Make changes to docstring

* Edit for efficiency

* Add credit to author

* Make changes to ShortMem

* Include ShortMem in _strategies.py

* Add tests for ShortMem

* Add paper to bibliography

* Fix error in docstring

* Word wrap to 80 columns

* Fix style issues

* Fix logical error in strategy and test

* Revert "Fix logical error in strategy and test"

This reverts commit a7b8d9f.

* Fix Readability

Author: janga1997

axelrod/strategies/_strategies.py

@@ -67,6 +67,7 @@
     Retaliate, Retaliate2, Retaliate3, LimitedRetaliate, LimitedRetaliate2,
     LimitedRetaliate3)
 from .sequence_player import SequencePlayer, ThueMorse, ThueMorseInverse
+from .shortmem import ShortMem
 from .titfortat import (
     TitForTat, TitFor2Tats, TwoTitsForTat, Bully, SneakyTitForTat,
     SuspiciousTitForTat, AntiTitForTat, HardTitForTat, HardTitFor2Tats,
@@ -208,6 +209,7 @@
     RevisedDowning,
     Ripoff,
     RiskyQLearner,
+    ShortMem,
     Shubik,
     SlowTitForTwoTats,
     SneakyTitForTat,

axelrod/strategies/shortmem.py

@@ -0,0 +1,49 @@
+from axelrod import Actions, Player
+from axelrod.actions import Action
+
+C, D = Actions.C, Actions.D
+
+class ShortMem(Player):
+    """
+    A player starts by always cooperating for the first 10 moves.
+    
+    From the tenth round on, the player analyzes the last ten actions, and
+    compare the number of defects and cooperates of the opponent, based in
+    percentage. If cooperation occurs 30% more than defection, it will
+    cooperate.
+    If defection occurs 30% more than cooperation, the program will defect.
+    Otherwise, the program follows the TitForTat algorithm.
+    
+    Names:
+    
+    - ShortMem: [Andre2013]_
+    """
+
+    name = 'ShortMem'
+    classifier = {
+        'memory_depth': 10,
+        'stochastic': False,
+        'makes_use_of': set(),
+        'long_run_time': False,
+        'inspects_source': False,
+        'manipulates_source': False,
+        'manipulates_state': False
+    }
+
+    @staticmethod
+    def strategy(opponent: Player) -> Action:
+        
+        if len(opponent.history) <= 10:
+            return C
+        
+        array = opponent.history[-10:]
+        C_counts = array.count('C')
+        D_counts = array.count('D')
+            
+        if C_counts - D_counts >= 3:
+            return C
+        elif D_counts - C_counts >= 3:
+            return D
+        else:
+            return opponent.history[-1]
+        

axelrod/tests/unit/test_shortmem.py

@@ -0,0 +1,35 @@
+"""Tests for the ShortMem strategy."""
+
+import axelrod
+from .test_player import TestPlayer
+
+C, D = axelrod.Actions.C, axelrod.Actions.D
+
+class TestCooperator(TestPlayer):
+
+    name = "ShortMem"
+    player = axelrod.ShortMem
+    expected_classifier = {
+        'memory_depth': 10,
+        'stochastic': False,
+        'makes_use_of': set(),
+        'inspects_source': False,
+        'manipulates_source': False,
+        'manipulates_state': False
+    }
+
+    def test_strategy(self):
+        # Starts by cooperating for the first ten moves.
+        self.responses_test([C], [C] * 4, [D] * 4)
+        self.responses_test([C], [C] * 9, [D] * 9)
+        self.responses_test([C], [C] * 4 + [D] *6, [D] * 4 + [C] * 6)
+        
+        #Cooperate if in the last ten moves, Cooperations - Defections >= 3
+        self.responses_test([C], [C] * 13 + [D] * 7, [D] * 16 + [C] * 7)
+            
+        #Defect if in the last ten moves, Defections - Cooperations >= 3
+        self.responses_test([D], [D] * 13 + [C] * 7, [C] * 12 + [D] * 8)
+        
+        #If neither of the above conditions are met, apply TitForTat 
+        self.responses_test([D], [C] * 13 + [D] * 7, [C] * 15 + [D] * 5)
+        self.responses_test([C], [C] * 17 + [D] * 7, [D] * 18 + [C] * 6)

docs/reference/bibliography.rst

@@ -37,3 +37,4 @@ documentation.
 .. [Stewart2012] Stewart, a. J., & Plotkin, J. B. (2012). Extortion and cooperation in the Prisoner’s Dilemma. Proceedings of the National Academy of Sciences, 109(26), 10134–10135. http://doi.org/10.1073/pnas.1208087109
 .. [Szabó1992] Szabó, G., & Fáth, G. (2007). Evolutionary games on graphs. Physics Reports, 446(4-6), 97–216. http://doi.org/10.1016/j.physrep.2007.04.004
 .. [Tzafestas2000] Tzafestas, E. (2000). Toward adaptive cooperative behavior. From Animals to Animals: Proceedings of the 6th International Conference on the Simulation of Adaptive Behavior {(SAB-2000)}, 2, 334–340.
+.. [Andre2013] Andre L. C., Honovan P., Felipe T. and Frederico G. (2013). Iterated Prisoner’s Dilemma - An extended analysis, http://abricom.org.br/wp-content/uploads/2016/03/bricsccicbic2013_submission_202.pdf