Branch of #1382 with new strategy

axelrod/strategies/_strategies.py

@@ -92,6 +92,7 @@
     TF2,
     TF3,
     EvolvedFSM4,
+    EvolvedFSM6,
     EvolvedFSM16,
     EvolvedFSM16Noise05,
     Fortress3,
@@ -337,6 +338,7 @@
     EvolvedFSM16,
     EvolvedFSM16Noise05,
     EvolvedFSM4,
+    EvolvedFSM6,
     EvolvedHMM5,
     EvolvedLookerUp1_1_1,
     EvolvedLookerUp2_2_2,

axelrod/strategies/finite_state_machines.py

@@ -1024,3 +1024,48 @@ def __init__(self) -> None:
         super().__init__(
             transitions=transitions, initial_state=0, initial_action=C
         )
+
+
+class EvolvedFSM6(FSMPlayer):
+    """
+    An 6 state FSM player trained with an evolutionary algorithm.
+
+    Evolved using axelrod-dojo version 0.0.8 and axelrod version 4.10.0, trained to maximize score against
+    the short_run_time_strategies with 10 machine states for 500 generations, population size of 40,
+    mutation rate at 0.1, bottleneck at 10, 200 turns, and 0 noise. The resulting strategy had only 6
+    states in its accessible component.
+
+    Names:
+
+        - Evolved FSM 6: Original name by Frederick Vincent & Dashiell Fryer
+    """
+
+    name = "Evolved FSM 6"
+    classifier = {
+        "memory_depth": float("inf"),
+        "stochastic": False,
+        "long_run_time": False,
+        "inspects_source": False,
+        "manipulates_source": False,
+        "manipulates_state": False,
+    }
+
+    def __init__(self) -> None:
+        transitions = (
+            (2, C, 2, D),
+            (2, D, 7, D),
+            (3, C, 6, D),
+            (3, D, 4, C),
+            (4, C, 4, C),
+            (4, D, 6, D),
+            (5, C, 2, D),
+            (5, D, 7, D),
+            (6, C, 3, C),
+            (6, D, 5, D),
+            (7, C, 2, C),
+            (7, D, 3, D),
+        )
+
+        super().__init__(
+            transitions=transitions, initial_state=4, initial_action=C
+        )

axelrod/tests/strategies/test_finite_state_machines.py

@@ -1101,6 +1101,26 @@ def test_strategy(self):
         self.versus_test(axl.Alternator(), expected_actions=actions)
 
 
+class TestEvolvedFSM6(TestFSMPlayer):
+
+    name = "Evolved FSM 6"
+    player = axl.EvolvedFSM6
+    expected_classifier = {
+        "memory_depth": float("inf"),
+        "stochastic": False,
+        "makes_use_of": set(),
+        "long_run_time": False,
+        "inspects_source": False,
+        "manipulates_source": False,
+        "manipulates_state": False,
+    }
+
+    def test_strategy(self):
+        player = self.player()
+        self.assertEqual(player.initial_state, 4)
+        self.assertEqual(player.initial_action, C)
+
+
 class TestEvolvableFSMPlayer(unittest.TestCase):
 
     player_class = EvolvableFSMPlayer

docs/index.rst

@@ -53,7 +53,7 @@ Count the number of available players::
 
     >>> import axelrod as axl
     >>> len(axl.strategies)
-    237
+    238
 
 Create matches between two players::