Big Bird is a (hopefully useful) package designed to facilitate the quick and convenient creation of basic genetic algorithms in python.
Results: https://drive.google.com/drive/folders/1REeKbD_3pZPEwbh0tRJNHyjC2MCwpfBG?usp=sharing
import bigbird
# Config Parameters for Big Bird
pop_size = 2000 # Size of each generation's population
layer_counts = [8, 5, 5, 3] # No. of nodes in each layer
m_r8 = 0.3 # Chance of weight mutation
step_ratio = 1/3.6 # Size of weight perturbation
reinit_r = 0.015 # Chance of weight reinitialization on mutation
immune = 20 # No. of non-mutated from top of previous generation
# When to automatically stop training
max_generation = 300
# Create a population with configuration parameters
population = bigbird.SimplePopulation(pop_size, layer_counts)
for generation in range(max_generation):
for bird in population.birds:
# Evaluates a bird's fitness based on a given input
bird_inp = your_input_generation_fn()
bird_out = bird.eval(bird_inp)
decision = output.tolist().index(max(output))
bird.fitness = your_fitness_fn(decision)
# Saves the best performing bird's weight matrices
champ = sorted(population.birds, key=lambda x: x.fitness)[-1]
champ.save(fname='./hall-of-fame/champ-' + str(generation) + '.json')
# Iniitializes next generation
population.store(immune)
population.breed()
population.mutate(m_r8, step_ratio, reinit=reinit_r)
population.retrieve()Find more examples here