Super Mario Neat

This program evolves an AI using the NEAT algorithm to play Super Mario Bros.
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Super Mario NEAT

This program uses the NEAT algorithm to evolve a Neural Network to play the original Super Mario Bros.


You can install the requirements by running

sudo apt install fceux
python3 -m pip install -r requirements.txt

Or if on windows, run

python3 -m pip install -r requirements.txt
  • Make sure you have FCEUX downloaded and added to PATH


The finisher.pkl file contains the best genome on generation 2284. In ./Files, you can find the backup for generation 2284, and the backup for generation 2492, which is where I stopped training.

You can continue training by running

python3 cont_train --gen <num_generations> --file <file>


To run the finisher.pkl file, run

python3 run

or run


If you want to run a different file, run

python3 run --file <file_name>


For debugging values, you can change any of the values in the config file. Note that you have to train from the 1st generation for some to take effect.
To use a different config file when training, specify --config <config file> when running


This program uses the build in python module multiprocessing, which is used for parallel computing. You can adjust the amount of genomes to run at once by specifying --parallel <num_of_genomes> when running


The default level is World 1, Level 1. This can be changed by specifying --level <level> when running For example,
python3 train --gen 100 --level "1-1" will use 1-1.


The finisher.pkl file is trained to complete 1-1. It can complete it around 50% of the time. The file keeps running the simulation until it completes the level. Ctrl + C will stop it.

Additional Information

The Wiki contains more information regarding the specifics of implementing certain parts.

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