Hands-On Neuroevolution with Python

Running the neuroevolution over the specified number of generations

At the beginning of this part, we create the intermediate variables to hold the execution results and create the statistics collector (Statistics). After that, we execute the evolution loop for the number of generations specified in the n_generations parameter:

    start_time = time.time()    best_genome_ser = None    best_ever_goal_fitness = 0    best_id = -1    solution_found = False    stats = Statistics()    for generation in range(n_generations):

Within the evolution loop, we obtain the list of genomes belonging to the population at the current generation and evaluate all genomes from the list against the test environment as follows:

        genomes = NEAT.GetGenomeList(pop) # evaluate genomes ...