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Auflistung nach Autor:in "Thielscher, Michael"

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  • Zeitschriftenartikel
    GDL-II
    (KI - Künstliche Intelligenz: Vol. 25, No. 1, 2011) Thielscher, Michael
    The Game Description Language (GDL) used in the past AAAI competitions allows to tell a system the rules of arbitrary finite games that are characterised by perfect information, but does not extend to games in which players have asymmetric information, e.g. about their own hand of cards, or which involve elements of chance like the roll of dice. Accordingly, contemporary general game-playing systems are not designed to play games such as Backgammon, Poker or Diplomacy. GDL-II (for: GDL with Incomplete/Imperfect Information) is a recent extension of the original description language that makes general game playing truly general, because it allows to describe just any finite game with arbitrary forms of randomness as well as imperfect/incomplete information. This brings along the challenge to build the next generation of truly general game-playing systems that are able to understand any game description given in GDL-II and to learn to master these types of games, too.
  • Zeitschriftenartikel
    Knowledge-Based General Game Playing
    (KI - Künstliche Intelligenz: Vol. 25, No. 1, 2011) Haufe, Sebastian; Michulke, Daniel; Schiffel, Stephan; Thielscher, Michael
    Although we humans cannot compete with computers at simple brute-force search, this is often more than compensated for by our ability to discover structures in new games and to quickly learn how to perform highly selective, informed search. To attain the same level of intelligence, general game playing systems must be able to figure out, without human assistance, what a new game is really about. This makes General Game Playing in ideal testbed for human-level AI, because ultimate success can only be achieved if computers match our ability to master new games by acquiring and exploiting new knowledge. This article introduces five knowledge-based methods for General Game Playing. Each of these techniques contributes to the ongoing success of our FLUXPLAYER (Schiffel and Thielscher in Proceedings of the National Conference on Artificial Intelligence, pp. 1191–1196, 2007), which was among the top four players at each of the past AAAI competitions and in particular was crowned World Champion in 2006.
  • Zeitschriftenartikel
    Special Issue on General Game Playing
    (KI - Künstliche Intelligenz: Vol. 25, No. 1, 2011) Thielscher, Michael