Evolution of an efficient search algorithm for the mate-in-N problem in chess

Ami Hauptman, Moshe Sipper

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

31 Scopus citations


We propose an approach for developing efficient search algorithms through genetic programming. Focusing on the game of chess we evolve entire game-tree search algorithms to solve the Mate-In-N problem: find a key move such that even with the best possible counterplays, the opponent cannot avoid being mated in (or before) move N. We show that our evolved search algorithms successfully solve several instances of the Mate-In-N problem, for the hardest ones developing 47% less game-tree nodes than CRAFTY - a state-of-the-art chess engine with a ranking of 2614 points. Improvement is thus not over the basic alpha-beta algorithm, but over a world-class program using all standard enhancements.

Original languageEnglish
Title of host publicationGenetic Programming - 10th European Conference, EuroGP 2007 Proceedings
PublisherSpringer Verlag
Number of pages12
ISBN (Print)3540716025, 9783540716020
StatePublished - 1 Jan 2007
Event10th European Conference on Genetic Programming, EuroGP 2007 - Valencia, Spain
Duration: 11 Apr 200713 Apr 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4445 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th European Conference on Genetic Programming, EuroGP 2007


  • Search Algorithm
  • Search Tree
  • Game Tree
  • Human Player
  • Chess Player

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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