new selections need to set a time limit

car.py

@@ -24,7 +24,7 @@ class Car(pygame.sprite.Sprite):
         self.rect = self.image.get_rect()
         self.vision_length = VISION_LENGTH # line liength
         self.vision_span = VISION_SPAN # degrees
-        self.draw_sensors = True
+        self.draw_sensors = False
 
         # lets add 3 sensors as a start 
         # 1 straight ahead
@@ -77,7 +77,7 @@ class Car(pygame.sprite.Sprite):
         self.rect.center = (self.speed * vec[0] / 2 + old_center[0], -self.speed * vec[1] / 2 + old_center[1])
         self.update_sensors()
         self.distance_run += int(distance(old_center, self.rect.center))
-        self.brain.fitness = math.sqrt(self.distance_run)
+        self.brain.fitness = int(math.sqrt(self.distance_run))
 
 
     
@@ -89,6 +89,7 @@ class Car(pygame.sprite.Sprite):
                 ip = segments_intersection(sensor, line)
                 # print(ip)
                 if ip :
+                    if self.draw_sensors :
                         pygame.draw.circle(screen, (125,125,255), ip, 4, 2)
                     dist = int(distance(ip,self.rect.center))
                     self.probes[idx] = min(dist, self.probes[idx])

genetics.py

@@ -1,11 +1,37 @@
 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])
+    parents_pool = []
+    half_pop = int(len(brains)/2)
 
+    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
@@ -15,14 +41,14 @@ def genetic_selection(brains):
 
         
         tot_fitness = len(wheel)
-    half_pop = int(len(brains)/2)
 
         # selection of pool/2 pair of parents to reproduce  
-    parents_pool = []
         for _ in range(half_pop):
+            idx1 = round(random.random()*tot_fitness - 1)
+            idx2 = round(random.random()*tot_fitness - 1)
             parents_pool.append([
-                wheel[round(random.random()*tot_fitness)], 
+                wheel[idx1], 
-                wheel[round(random.random()*tot_fitness)]
+                wheel[idx2]
                 ])
     return parents_pool
     

main.py

@@ -62,8 +62,8 @@ def run_round(all_cars):
     all_cars.empty()
     for b in new_brains :
         all_cars.add(Car(brain=b))
-    print("Waiting 5 secs before new run")
+    print("Waiting before new run")
-    for x in range(10) :
+    for x in range(1) :
         time.sleep(0.5)
         pygame.display.flip()
 

params.py

@@ -7,14 +7,16 @@ GX                      = 1000
 GY                      = 1000
 CELL_COLOR              = (80,80,80)
 CAR_SIZE                = 20
-CAR_MAX_SPEED           = 6
+CAR_MAX_SPEED           = 100
-CAR_MAX_FITNESS         = 5000
+CAR_MAX_FITNESS         = 100
 CAR_STEERING_FACTOR     = 10
 VISION_LENGTH           = 60
 VISION_SPAN             = 35 # degrees
 THROTTLE_POWER          = 3
 
 MUTATION_RATE           = 0.01
+SELECTION_ALG           = "kway" # roulette
+KWAY_TOURNAMENT_PLAYERS = 3
 
 pygame.init()
 screen = pygame.display.set_mode((GX, GY), FLAGS)