Specialized vs. Multi-game Approaches to AI in Games

  • Maciej ŚwiechowskiEmail author
  • Jacek Mańdziuk
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 322)


In this work, we identify the main problems in which methodology of creating multi-game playing programs differs from single-game playing programs. The multi-game framework chosen in this comparison is General Game Playing, which was proposed at Stanford University in 2005, since it defines current state-of-the-art trends in the area. Based on the results from the International General Game Playing Competitions and additional results of our agent named MINI-Player we conclude on what defines a successful player. The most successful players have been using a minimal knowledge and a mechanism called Monte Carlo Tree-Search, which is simulation-based and self-improving over time.


Games Artificial Intelligence General Game Playing Heuristic Search 


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© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Phd Studies at Systems Research InstitutePolish Academy of SciencesWarsawPoland
  2. 2.Faculty of Mathematics and Information ScienceWarsaw University of TechnologyWarsawPoland

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