Abstract
Recently, it has been shown that lexicographic orderings and time travel can be used to automate the play of Nintendo Entertainment System (NES) games. In this work, we present a method for optimizing solutions to NES games. Since many of these classic Nintendo games are NP-hard, we propose a metaheuristic algorithm that works by borrowing operators from evolutionary algorithms. By using a search based heuristic, the algorithm is able to create basic solutions to the games and then iteratively improve upon them until it converges towards a local maximum. The optimum game solutions found by this algorithm are shown to be competitive to human players and are close to the best known times achieved by them.
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