def evolve_generations_plateau(simulation_func, negligible, max_bad_gen_count, pop_size=60, num_fittest=5, num_random=10, num_elites=3):
# Create start generation
# While not done
# Simulate generation
# Check if should be done
# Spawn next generation
Generator = GenFFANN
num_params = (GenFFANN.INPUTSIZE * GenFFANN.HIDDENSIZE) + (GenFFANN.HIDDENSIZE * GenFFANN.OUTPUTSIZE)
print num_params
current_gen = Generation(Generator, simulation_func, pop_size, num_fittest, num_random, num_elites, num_params)
current_gen.spawn_random_generation()
best_fitness = -100000
bad_gen_count = 0
gen_num = 0
while True:
gen_num += 1
print "Running generation {0}".format(gen_num)
fitness = current_gen.run()
print "Fitness is {0} compared to {1}".format(fitness, best_fitness)
if fitness - best_fitness <= negligible:
bad_gen_count += 1
print "Bad Generation #{0}".format(bad_gen_count)
else:
bad_gen_count = 0
best_generator = current_gen.fittest[0]
best_fitness = best_generator.fitness
if bad_gen_count >= max_bad_gen_count:
return best_generator
current_gen = current_gen.spawn_next_generation()
