Symbolic Classification of General Multi-Player Games

  • Authors:
  • Peter Kissmann;Stefan Edelkamp

  • Affiliations:
  • Dortmund University of Technology, Germany, email: peter.kissmamn@cs.uni-dortmund.de;Dortmund University of Technology, Germany, email: peter.kissmamn@cs.uni-dortmund.de

  • Venue:
  • Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
  • Year:
  • 2008

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Abstract

For general two-player turn-taking games, first solvers have been contributed. Algorithms for multi-player games like Maxn, however, cannot classify general games robustly, and its extension Soft-Maxn, which can play optimally against unknown and weak opponents, demands large amounts of memory. As RAM is a scarce resource, this paper proposes a memory-efficient implementation of the Soft-Maxn algorithm, by exploiting the functional representation of state and evaluation sets with BDDs.