Abstract
Years of work have gone into algorithms and optimizations for two-player perfect-information games such as Chess and Checkers. It is only more recently that serious research has gone into games with imperfect information, such as Bridge, or game with more than two players or teams of players, such as Poker. This work focuses on multi-player game search in the card games Hearts and Spades, providing an overview of past research in multi-player game search and then presents new research results regarding the optimality of current search techniques and the need for good opponent modeling in multi-player game search. We show that we are already achieving near-optimal pruning in the games Hearts and Spades.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hu, F.: Behind Deep Blue. Princeton University Press, Princeton (2002)
Schaeffer, J., Culberson, J., Treloar, N., Knight, B., Lu, P., Szafron, D.: A world championship caliber checkers program. Artificial Intelligence 53, 273–290 (1992)
Billings, D., Peña, L., Schaeffer, J., Szafron, D.: Using Probabilistic Knowledge and Simulation to Play Poker. In: AAAI 1999, pp. 697–703 (1999)
Ginsberg, M.: GIB. Imperfect Information in a Computationally Challenging Game. Journal of Artificial Intelligence Research 14, 303–358 (2001)
Knuth, D., Moore, R.: An Analysis of Alpha-Beta Pruning. Artificial Intelligence 6(4), 293–326 (1975)
Russell, S.J., Wefald, E.H.: On optimal game-tree search using rational meta-reasoning. In: IJCAI 1989, Detroit, MI, pp. 334–340 (1989)
Carmel, D., Markovitch, S.: Incorporating Opponent Models into Adversary Search. In: AAAI 1996, Portland, OR (1996)
Nash, J.F.: Non-cooperative games. Annals of Mathematics 54, 286–295 (1951)
Jones, A.J.: Game Theory: Mathematical Models of Conflict. Ellis Horwood, West Sussex (1980)
Kuhn, H.W.: Extensive Games and the Problem of Information. In: Kuhn, Tucker (eds.) Contributions to the Theory of Games. Princeton University Press, New Jersey (1953)
Luckhardt, C., Irani, K.: An algorithmic solution of N-person games. In: AAAI 1986, Philadelphia, PA, pp. 158–162 (1986)
Luckhardt, C.: N-Person Game Playing and Artificial Intelligence. PhD. Thesis, University of Michigan (1989)
Mutchler, D.: The Multi-Player Version of Minimax Displays Game-Tree Pathology. Artificial Intelligence 64, 323–336 (1993)
Nao, D.S.: Pathology on game trees: A summary of results. In: AAAI 1980, Stanford, CA, pp. 102–104 (1980)
Beal, D.F.: An analysis of Minimax. In: Clarke, M.R.B. (ed.) Advances in Computer Chess, vol. 2, pp. 103–109. Edinburgh University Press, Edinburgh (1980)
Korf, R.: Multiplayer Alpha-Beta Pruning. Artificial Intelligence 48(1), 99–111 (1991)
Sturtevant, N., Korf, R.: On Pruning Techniques for Multi-Player Games. In: AAAI 2000, Austin, TX, pp. 201–207 (2000)
Sturtevant, N.: A Comparison of Algorithms for Multi-Player Games. In: Schaeffer, Müller, Björnsson (eds.) Proceedings of the 3rd International Conference on Computers and Games, pp. 108–122 (2002)
Pearl, J.: Heuristics. Addison-Wesley, Reading (1984)
Sturtevant, N.: Last-Branch and Speculative Pruning Algorithms for Maxn. In: Mobasher, B., Anand, S.S. (eds.) ITWP 2003. LNCS (LNAI), vol. 3169. Springer, Heidelberg (2005)
Sturtevant, N.: Multi-Player Games: Algorithms and Approaches. PhD Thesis, UCLA (2003)
Hoyle, E., Frey, R.L., Morehead, A.L., Mott-Smith, G.: The Authoritative Guide to the Official Rules of All Popular Games of Skill and Chance, Doubleday (1991)
Schaeffer, J.: The History Heuristic and Alpha-Beta Enhancements in Practice. IEEE Transactions on Pattern Analysis and Machine Intelligence 11(11), 1203–1212 (1989)
Jansen, P.: Problematic Positions and Speculative Play. In: Computers, Chess and Cognition, pp. 169–182. Springer, New York (1990)
Iida, H., Uiterwijk, J.W.H.M., van den Herik, H.J., Herschberg, I.S.: Potential Applications of Opponent-Model Search, Part 1: The domain of applicability. ICCA Journal 16(4), 201–208 (1993)
Iida, H., Uiterwijk, J.W.H.M., van den Herik, H.J., Herschberg, I.S.: Potential Applications of Opponent-Model Search, Part 2: Risks and Strategies. ICCA Journal 17(1), 10–14 (1994)
Korf, R.: Generalized Game Trees. In: IJCAI 1989, pp. 328–333 (1989)
Donkers, H.H.L.M., Uiterwijk, J.W.H.M., Herik, H.J.: Probabilistic Opponent-Model Search. Information Sciences 135(3-4), 123–149 (2001)
Donkers, H.H.L.M.: Nosce Hostem: Searching with Opponent Models. PhD Thesis, University of Maastricht (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sturtevant, N. (2006). Current Challenges in Multi-player Game Search. In: van den Herik, H.J., Björnsson, Y., Netanyahu, N.S. (eds) Computers and Games. CG 2004. Lecture Notes in Computer Science, vol 3846. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11674399_20
Download citation
DOI: https://doi.org/10.1007/11674399_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32488-1
Online ISBN: 978-3-540-32489-8
eBook Packages: Computer ScienceComputer Science (R0)