What #VideoGames can do for #AI
Posted on May 28th, 2017
05/25/2017 @ Galvanize, 315 Hudson Street, NY, 2nd floor
Julian Togelius @NYU spoke about the state of competitions to create controllers to play video games. Much of what he talked about is contained in his paper on The #Mario AI Championship 2009-2012
The first winner in 2009 used an A* search of the action space. The A* algorithm is a complete search of the graph of possible actions prioritizing the search based on the distance from the origin to each current node + the estimated distance from each current node to the goal.
The contest in 2010 was won by Bojarski & Congdon – #Realm using a rule based agent
The competition has expanded to include a trying to create Bayesian networks to play Mario Brothers like a human: Togelius & Yannakakis 2012. See https://pdfs.semanticscholar.org/2d0b/34e31f02455c2d370a84645b295af6d59702.pdf
Another part of the competition seeks to create programs that can play multiple games and carry their learning from one game to the next as opposed to custom programs can only play a single game
Therefore they created a general video game playing competition – games written in Video Game Description Language. (http://people.idsia.ch/~tom/publications/pyvgdl.pdf) Programs are written in Java and access a competition API.
The programs are split into two competitions
- Get the framework, but cannot train – solutions are variations on search
- Do not get the framework, but can train the network – solutions are closer to neural nets