running

brain.py

@@ -14,9 +14,14 @@ class Neural_Network(object):
         self.fitness = 0 
 
         #weights
-        if not W1 :
+        if W1 is not None:
+            self.W1=W1
+        else :
             self.W1 = np.random.randn(self.inputSize, self.hiddenSize) # weights from input to hidden layer
-        if not W2 :
+        
+        if W2 is not None:
+            self.W2=W2
+        else :
             self.W2 = np.random.randn(self.hiddenSize, self.outputSize) # weights from hidden to output layer
         # self.w1 = [[random.random() for i in range(self.hiddenSize)] for i in range(self.inputSize)]
         # self.w2 = [[random.random() for i in range(self.outputSize)] for i in range(self.hiddenSize)]

car.py

@@ -1,4 +1,5 @@
 import numpy as np
+import random
 import pygame
 
 from brain import Neural_Network
@@ -9,7 +10,7 @@ IMG = pygame.image.load("car20.png")#.convert()
 
 
 class Car(pygame.sprite.Sprite):
-    def __init__(self):
+    def __init__(self, brain=None):
         pygame.sprite.Sprite.__init__(self)
         self.top_surface = pygame.Surface((CAR_SIZE, CAR_SIZE))
         self.original_image = IMG
@@ -21,9 +22,6 @@ class Car(pygame.sprite.Sprite):
 
         self.rect = self.image.get_rect()
         self.rect.center = (75, GY -50)
-        self.speed = 1
-        self.heading = 0
-        self.heading_change = 0
         self.vision_length = VISION_LENGTH # line liength
         self.vision_span = VISION_SPAN # degrees
         self.draw_sensors = True
@@ -41,12 +39,20 @@ class Car(pygame.sprite.Sprite):
         self.sensors = [self.left_sensor, self.center_sensor, self.right_sensor]
         self.probes = [self.vision_length] *3 
         
-        self.brain = Neural_Network()
+        if brain :
+            self.brain = brain
+        else :
+            self.brain = Neural_Network()
         
+        self.reset_car_pos()
         self.update_sensors()
         self.probe_brain()
         self.run = True
 
+    def reset_car_pos(self):
+        self.speed = 1
+        self.heading = 0
+        self.heading_change = random.random() * 30
 
     def update_sensors(self):
         center = self.rect.center
@@ -83,7 +89,8 @@ class Car(pygame.sprite.Sprite):
                     if dist < 1.2 * self.speed or self.speed < 0.01 :
                         self.run = False
                         self.speed = 0
-                        print(f'Car {id(self)} crashed')
+                        # print(f'Car {id(self)} crashed')
+                        return
 
                 # else :
                 #     self.probes[idx] = self.vision_length * 2 
@@ -106,13 +113,13 @@ class Car(pygame.sprite.Sprite):
         if self.speed < 0.01 :
             self.run = False
             print(f'Car {id(self)} crashed')
-        print(
-            'id', id(self),
-            'Speed', self.speed,
-            'heading', self.heading,
-            'throttle', self.throttle,
-            'heading change', self.heading_change,
-        )
+        # print(
+        #     'id', id(self),
+        #     'Speed', self.speed,
+        #     'heading', self.heading,
+        #     'throttle', self.throttle,
+        #     'heading change', self.heading_change,
+        # )
 
         if self.speed : 
             self.heading += self.heading_change * CAR_STEERING_FACTOR / self.speed 

genetics.py

@@ -10,7 +10,7 @@ def genetic_selection(brains):
     # proportionnally to its relative fitness
     wheel = []
     for b in brains :
-        wheel += [b] * b.brains
+        wheel += [b] * b.fitness
 
     
     tot_fitness = len(wheel)
@@ -19,7 +19,11 @@ def genetic_selection(brains):
     # selection of pool/2 pair of parents to reproduce  
     parents_pool = []
     for _ in range(half_pop):
-        parents_pool.append([round(random.random()*tot_fitness), round(random.random()*tot_fitness)])
+        parents_pool.append([
+                wheel[round(random.random()*tot_fitness)], 
+                wheel[round(random.random()*tot_fitness)]
+                ])
+    return parents_pool
     
 
 def cross_mutate_genes(p1_gene, p2_gene):
@@ -28,15 +32,15 @@ def cross_mutate_genes(p1_gene, p2_gene):
     p2_gene = list(p1_gene)
     for idx,x in enumerate(p2_gene):
         if random.random() > 0.5 :
-            choice = p1_gene
+            choice = p1_gene[idx]
         else :
-            choice = p2_gene
+            choice = p2_gene[idx]
         # Mutation
         if random.random() < 0.005 :
-            choice[random.randint(0, len(choice - 1))] = random.random()
+            choice[random.randint(0, len(choice) - 1)] = random.random()
             print("Mutation !")
-        child.append(np.array(choice))
-    return child
+        child.append(choice)
+    return np.array(child)
 
 
 def genetic_reproduction(parents_pool):

main.py

@@ -2,13 +2,17 @@
 import math
 import pygame
 import random
+import time
 
 from car import Car
+from genetics import genetic_selection, genetic_reproduction
 from maps import map1
 from params import CELL_COLOR, screen
 
 
+
 #https://medium.com/intel-student-ambassadors/demystifying-genetic-algorithms-to-enhance-neural-networks-cde902384b6e
+clock = pygame.time.Clock()
 
 
 map_lines = map1
@@ -19,33 +23,52 @@ all_cars = pygame.sprite.Group()
 
 for x in range(100):
     car = Car()
-    car.heading = x * 30 + 35
     all_cars.add(car)
 
-clock = pygame.time.Clock()
-running_cars = True
-while running_cars :
-    running_cars = False
-    screen.fill(CELL_COLOR)
-    all_cars.draw(screen)
-    for c in all_cars :
-        c.show_features()
-        if c.run :
-            running_cars = True
-            c.probe_lines_proximity(map_lines)
-            c.probe_brain()
-            c.update()
 
-    for line in map_lines :
-        pygame.draw.line(screen, (255,255,255), line[0], line[1])
+def run_round(all_cars):
+    running_cars = True
+    while running_cars :
+        running_cars = False
+        screen.fill(CELL_COLOR)
+        all_cars.draw(screen)
+        for c in all_cars :
+            c.show_features()
+            if c.run :
+                running_cars = True
+                c.probe_lines_proximity(map_lines)
+                c.probe_brain()
+                c.update()
 
+        for line in map_lines :
+            pygame.draw.line(screen, (255,255,255), line[0], line[1])
 
-    pygame.display.flip()
-    clock.tick(24)
+        pygame.display.flip()
+        clock.tick(48)
+
+    # for c in all_cars :
+    #     print(f"Car {id(c)} Fitness : {c.brain.fitness})")
+    
+    print('Collecting brains')
+    brains = [c.brain for c in all_cars]
+    print(f"Max fitness = {max([b.fitness for b in brains])}" )
+    print(f"Avg fitness = {sum([b.fitness for b in brains])/len(brains)}" )
+    print('selecting')
+    parents_pool = genetic_selection(brains)
+    # import ipdb; ipdb.set_trace()
+    print("breeding")
+    new_brains = genetic_reproduction(parents_pool)
+    print(f'building {len(new_brains)} cars with new brains')
+    all_cars.empty()
+    for b in new_brains :
+        all_cars.add(Car(brain=b))
+    print("Waiting 5 secs before new run")
+    for x in range(10) :
+        time.sleep(0.5)
+        pygame.display.flip()
 
-for c in all_cars :
-    print(f"Car {id(c)} Fitness : {c.brain.fitness})")
 
 while True :
+    run_round(all_cars)
     pygame.display.flip()
     clock.tick(24)

params.py

@@ -10,7 +10,7 @@ CAR_SIZE                = 20
 CAR_MAX_SPEED           = 7
 CAR_STEERING_FACTOR     = 10
 VISION_LENGTH           = 50
-VISION_SPAN             = 25 # degrees
+VISION_SPAN             = 35 # degrees
 THROTTLE_POWER          = 3