77 lines
2.0 KiB
Python
Executable File
77 lines
2.0 KiB
Python
Executable File
#!/usr/bin/env python
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import math
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import pygame
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import random
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import time
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from car import Car
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from genetics import genetic_selection, genetic_reproduction
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from maps import map1
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from params import CELL_COLOR, GX, GY, screen
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# https://medium.com/intel-student-ambassadors/demystifying-genetic-algorithms-to-enhance-neural-networks-cde902384b6e
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clock = pygame.time.Clock()
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font = pygame.font.SysFont("hack", 24)
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map_lines = map1
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all_cars = pygame.sprite.Group()
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for x in range(100):
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car = Car()
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all_cars.add(car)
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def run_round(all_cars):
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running_cars = True
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while running_cars:
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running_cars = False
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screen.fill(CELL_COLOR)
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all_cars.draw(screen)
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for c in all_cars:
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c.show_features()
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if c.run:
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running_cars = True
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c.probe_lines_proximity(map_lines)
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c.probe_brain()
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c.update()
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for line in map_lines:
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pygame.draw.line(screen, (255, 255, 255), line[0], line[1])
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text = font.render(f"Generation {loop}", True, (128, 128, 128))
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screen.blit(text, (GX - 50 - text.get_width(), text.get_height() // 2))
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pygame.display.flip()
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clock.tick(48)
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# for c in all_cars :
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# print(f"Car {id(c)} Fitness : {c.brain.fitness})")
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print("Collecting brains")
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brains = [c.brain for c in all_cars]
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print(f"Max fitness = {max([b.fitness for b in brains])}")
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print(f"Avg fitness = {sum([b.fitness for b in brains])/len(brains)}")
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print("selecting")
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parents_pool = genetic_selection(brains)
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# import ipdb; ipdb.set_trace()
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print("breeding")
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new_brains = genetic_reproduction(parents_pool)
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print(f"building {len(new_brains)} cars with new brains")
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all_cars.empty()
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for b in new_brains:
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all_cars.add(Car(brain=b))
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print("Waiting before new run")
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for x in range(1):
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time.sleep(0.5)
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pygame.display.flip()
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loop = 0
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while True:
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loop += 1
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run_round(all_cars)
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# pygame.display.flip()
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# clock.tick(24)
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