Applying Saved Neat-python Genome To Test Environment After Training

I have used some NEAT algorithms to code my own AI for some easy games like flappy bird. Everything works fine and I know what is going on. The problem is I do not know what to do

Solution 1:

I assume that the code you supplied is not your own and that you were following some sort of tutorial. The quality of the code is very low, documentation in form of comments is literally non-existent and variable naming is not english. If you coded that, than that's completely fine for a beginner. Actually even impressive. Though especially for a beginner's tutorial do I highly recommend to search for better explained and documented tutorials.

With that being said, here is the code that you need to add to your project in order to replay a saved genome:

defreplay_genome(config_path, genome_path="winner.pkl"):
    # Load requried NEAT config
    config = neat.config.Config(neat.DefaultGenome, neat.DefaultReproduction, neat.DefaultSpeciesSet, neat.DefaultStagnation, config_path)

    # Unpickle saved winnerwithopen(genome_path, "rb") as f:
        genome = pickle.load(f)

    # Convert loaded genome into required data structure
    genomes = [(1, genome)]

    # Call game with only the loaded genome
    game(genomes, config)

Obviously as the code quality was quite low was I unable to understand it to such a degree to provide a clean replay code. Therefore the code is simply reusing the existing game code to train the population, though the population consists only of the loaded genome in this case.

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