Recognizing Seki in Computer Go

  • Xiaozhen Niu
  • Akihiro Kishimoto
  • Martin Müller
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4250)


Seki is a situation of coexistence in the game of Go, where neither player can profitably capture the opponent’s stones. This paper presents a new method for deciding whether an enclosed area is or can become a seki. The method combines local search with global-level static analysis. Local search is used to identify possible seki, and reasoning on the global level is applied to determine which stones are safe with territory, which coexist in a seki and which are dead. Experimental results show that a safety-of-territory solver enhanced by this method can successfully recognize a large variety of local and global scale test positions related to seki. In contrast, the well-known program GNU Go can only solve easier problems from a test collection.


Local Search Static Rule Global Search Local Search Algorithm White Region 
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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  1. 1.
    Allis, L.V., Meulen, M., van den Herik, H.J.: Proof-Number Search. Artificial Intelligence 66(1), 91–124 (1994)MATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Benson, D.B.: Life in the Game of Go. Information Sciences 10, 17–29 (1976); Reprinted in Levy, D.N.L. (ed.): Computer Games, vol. II, pp. 203–213. Springer, New York (1988) Google Scholar
  3. 3.
    Campbell, M.: The Graph-History Interaction: On Ignoring Position History. In: Association for Computing Machinery Annual Conference, pp. 278–280 (1985)Google Scholar
  4. 4.
    Chen, K., Chen, Z.: Static Analysis of Life and Death in the Game of Go. Information Science 121, 113–134 (1999)CrossRefGoogle Scholar
  5. 5.
    Kishimoto, A.: Correct and Efficient Search Algorithms in the Presence of Repetitions. PhD thesis, Department of Computing Science, University of Alberta (2005)Google Scholar
  6. 6.
    Kishimoto, A., Müller, M.: DF-PN in Go: Application to the One-Eye Problem. In: van den Herik, H.J., Iida, H., Heinz, E.A. (eds.) 10th Advances in Computer Games (ACG10), Many Games, Many Challenges, pp. 125–141. Kluwer Academic Publishers, Boston (2004)Google Scholar
  7. 7.
    Kishimoto, A., Müller, M.: A General Solution to the Graph History Interaction Problem. In: 19th National Conference on Artificial Intelligence (AAAI 2004), pp. 644–649. AAAI Press, Menlo Park (2004)Google Scholar
  8. 8.
    Müller, M.: Computer Go as a Sum of Local Games: An Application of Combinatorial Game Theory. PhD thesis, Diss. ETH Nr. 11.006, ETH Zürich (1995)Google Scholar
  9. 9.
    Müller, M.: Playing it Safe: Recognizing Secure Territories in Computer Go by Using Static Rules and Search. In: Matsubara, H. (ed.) Game Programming Workshop in Japan 1997, pp. 80–86. Computer Shogi Association, Tokyo, Japan (1997)Google Scholar
  10. 10.
    Müller, M.: Race to Capture: Analyzing Semeai in Go. In: Game Programming Workshop in Japan. IPSJ Symposium Series, vol. 99(14), pp. 61–68 (1999)Google Scholar
  11. 11.
    Nagai, A.: DF-PN Algorithm for Searching AND/OR Trees and Its Applications. PhD thesis, Department of Information Science, University of Tokyo (2002)Google Scholar
  12. 12.
    Niu, X., Müller, M.: An Improved Safety Solver for Computer Go. In: van den Herik, H.J., Björnsson, Y., Netanyahu, N.S. (eds.) CG 2004. LNCS, vol. 3846, pp. 97–112. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Palay, A.J.: Searching with Probabilities. PhD thesis, Carnegie Mellon University (1983)Google Scholar
  14. 14.
    Tao, S.: Guan Zi Pu (1689); Reprinted in Shu Rong Qi Yi Chu Ban She. Da Quan, W.Q.J.Q., MingJiu, J., ZhuJiu, J. (eds.), Cheng Du, China (1996)Google Scholar
  15. 15.
    van der Werf, E., van den Herik, H.J., Uiterwijk, J.W.H.M.: Learning to Score Final Positions in the Game of Go. In: van den Herik, H.J., Iida, H., Heinz, E.A. (eds.) 10th Advances in Computer Games (ACG10), Many Games, Many Challenges, pp. 143–158. Kluwer Academic Publishers, Boston (2004)Google Scholar
  16. 16.
    Vilà, R., Cazenave, T.: When One Eye is Sufficient: a Static Classification. In: van den Herik, H.J., Iida, H., Heinz, E.A. (eds.) 10th Advances in Computer Games (ACG10), Many Games, Many Challenges, pp. 109–124. Kluwer Academic Publishers, Boston (2004)Google Scholar
  17. 17.
    van der Werf, E.: AI Techniques for the Game of Go. PhD thesis, University of Maastricht (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xiaozhen Niu
    • 1
  • Akihiro Kishimoto
    • 2
  • Martin Müller
    • 1
  1. 1.Department of Computing ScienceUniversity of AlbertaEdmontonCanada
  2. 2.Department of Media ArchitectureFuture University-HakodateHakodate, HokkaidoJapan

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