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Super Mario World playing agent developed using Retro Learning Environment library as a final project for the Machine Learning course at Universidade Federal do ABC.

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Super Mario NEAT

Super Mario World playing agent developed using Retro Learning Environment library as a final project for the Machine Learning course at Universidade Federal do ABC.

This agent uses Neuroevolution of Augmenting Topologies (NEAT) in order to evolve a Neural Network capable of playing the stage.

For install requirements:

pip install -r requirements.txt
  • Run evolve.py. When it completes, it will have created winner, a pickled version of the most fit genome.

  • Run play.py. It will load the most fit genome from winner and run it in a new simulation to show the behavior. (See a sample movie here.)

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Super Mario World playing agent developed using Retro Learning Environment library as a final project for the Machine Learning course at Universidade Federal do ABC.

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