Learning To Play Mario Bros.

August 6, 2009

Julian Togelius and Sergey Karakovskiy have organized a competition to create an agent (or AI) that plays the video game Super Mario Bros. – or, more accurately, Infinite Mario Bros. a tribute game featuring random level generation.

The advantage of using Infinite Mario Bros. is the random level generation – which can let the agent learn more generalized playing tactics rather than tactics that are tailored to a static set of levels as in Ms. Pac-Man or Pitfall.

I look forward to seeing the results of the competition, and hope to see source code published as well.

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Posted by Karl W. Reinsch

A Computer That Plays Pitfall

June 29, 2009

From Rutgers university comes a learning algorithm that they have applied to playing the Atari 2600 game “Pitfall!”.

An example video is on YouTube.

One of the research papers is apparently here (although the site isn’t being very responsive at the moment).

I’ll get around to posting on machine learning for Pac-Man/Ms. Pac-Man at some point as well.

(Spotted on Kotaku and GameSetWatch.)

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Posted by Karl W. Reinsch