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Mathematical Methods of Operations Research

, Volume 64, Issue 1, pp 79–93 | Cite as

Error Propagation in Game Trees

  • Benjamin Doerr
  • Ulf Lorenz
Original Article

Abstract

Game tree search is the core of most attempts to make computers play games. We present a fairly general theoretical analysis on how leaf evaluation errors influence the value estimation of a game position at the root. By an approach using prime factorization arguments in the ring of polynomials, we show that in this setting the maximum number of leaf-disjoint strategies proving a particular property is a key notion. This number precisely describes the quality of the heuristic game value in terms of the quality of the leaf evaluation heuristics. We extend this model to include random nodes (rolls of a die). Surprisingly, this changes the situation: utill the number of leaf-disjoint strategies ensures robustness against leaf evaluation errors, but the converse is not true. An average node may produce additional robustness similar to additional leaf-disjoint strategies. This work extends earlier ones which only deal with 0, 1 valued nodes, or without randomness.

Keywords

Game Tree Random Node Minimax Principle Chess Game Game Position 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Benjamin Doerr
    • 1
  • Ulf Lorenz
    • 2
  1. 1.Mathematisches Seminar IIChristian–Albrechts–Universität zu KielKielGermany
  2. 2.Department of Mathematics and Computer SciencePaderborn UniversityPaderbornGermany

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