new selections need to set a time limit

genetics.py

@@ -1,28 +1,54 @@
 import numpy as np
 import random
 from brain import Neural_Network
-from params import MUTATION_RATE
+from params import MUTATION_RATE, SELECTION_ALG, KWAY_TOURNAMENT_PLAYERS
+
+def kway_selection(brains, exclude=None):
+    tourn_pool = []
+    best_play = None
+    if exclude :
+        brains = [x for x in brains if x != exclude]
+    for x in range(KWAY_TOURNAMENT_PLAYERS):
+        new_play = random.choice(brains)
+        while new_play in tourn_pool :
+            new_play = random.choice(brains)
+        if not best_play or best_play.fitness < new_play.fitness :
+            best_play = new_play
+    return best_play
 
 def genetic_selection(brains):
-    # tot_fitness = sum ([int(b.fitness) for b in brains])
-
-    # does not seem very optimized... TBR
-    # constitute a list where every brain is represented
-    # proportionnally to its relative fitness
-    wheel = []
-    for b in brains :
-        wheel += [b] * b.fitness
-
-    
-    tot_fitness = len(wheel)
+    parents_pool = []
     half_pop = int(len(brains)/2)
 
-    # selection of pool/2 pair of parents to reproduce  
-    parents_pool = []
-    for _ in range(half_pop):
-        parents_pool.append([
-                wheel[round(random.random()*tot_fitness)], 
-                wheel[round(random.random()*tot_fitness)]
+    if SELECTION_ALG == "kway":
+        for x in range(half_pop) :
+            p1 = kway_selection(brains)
+            p2 = kway_selection(brains, exclude=p1)
+            parents_pool.append([
+                p1, 
+                p2
+            ])
+
+
+
+    elif SELECTION_ALG == "roulette" :
+        # does not seem very optimized... TBR
+        # constitute a list where every brain is represented
+        # proportionnally to its relative fitness
+        wheel = []
+        for b in brains :
+            wheel += [b] * b.fitness
+
+        
+        tot_fitness = len(wheel)
+
+        # selection of pool/2 pair of parents to reproduce  
+        for _ in range(half_pop):
+            idx1 = round(random.random()*tot_fitness - 1)
+            idx2 = round(random.random()*tot_fitness - 1)
+            parents_pool.append([
+                wheel[idx1], 
+                wheel[idx2]
                 ])
     return parents_pool