With the introduction of computers, also started the interest in having machines play games. Programming a computer such that it could play, for example chess, was seen as giving it some kind of intelligence. Starting in the mid fifties, a theory on how to play two player zero sum perfect information games, like chess or go, was developed. This theory is essentially based on traversing a tree called minimax or game tree. An edge in the tree represents a move by either of the players and a node a configuration of the game.
Two major algorithms have emerged to compute the best sequence of moves in such a minimax tree. On one hand, there is the alpha-beta algorithm suggested around 1956 by I. McCarthy and first published in [27]. On the other hand, G.C. Stockman [29] introduced the SSS∗ algorithm. Both methods try to minimize the number of nodes explored in the game tree using special traversal strategies and cut conditions.
Minimax Trees
A...
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Akl, S. G., Barnard, D. T., and Doran, R. J.: ‘Searching game trees in parallel’: Proc. 3rd Biennial Conf. Canad. Soc. Computation Studies of Intelligence, 1979, pp. 224–231.
Akl, S. G., Barnard, D. T., and Doran, R. J.: ‘Design, analysis, and implementation of a parallel tree search algorithm’, IEEE Trans. Pattern Anal. Machine Intell.PAMI-4, no. 2 (1982), 192–203.
Almquist, K., McKenzie, N., and Sloan, K.: ‘An inquiry into parallel algorithms for searching game trees’, Techn. Report Univ. Washington, Seattle, WA12, no. 3 (1988).
Althöfer, I.: ‘On the complexity of searching game trees and other recursion trees’, J. Algorithms9 (1988), 538–567.
Althöfer, I.: ‘An incremental negamax algorithm’, Artif. Intell.43 (1990), 57–65.
Ballard, B. W.: ‘The ∗-minimax search procedure for trees containing chance nodes’, Artif. Intell.21 (1983), 327–350.
Baudet, G. M.: ‘The design and analysis of algorithms for asynchronous multiprocessors’, PhD Thesis Carnegie-Mellon Univ. Pittsburgh, PA no. CMU-CS-78-116 (1978).
Böhm, M., and Speckenmeyer, E.: ‘A dynamic processor tree for solving game trees in parallel’, Proc. SOR’89, 1989.
Cung, V.-D, and Roucairol, C.: ‘Parallel minimax tree searching’, Res. Report INRIA1549 (1991). (In French.)
Diderich, C. G.: ‘Evaluation des performances de l’algorithme SSS∗ avec phases de synchronisation sur une machine parallèle à mémoires distribuées’, Techn. Report Computer Sci. Dept. Swiss Federal Inst. Techn. Lausanne, Switzerland no. LiTH-99 (July 1992). (In French.)
Feigenbaum, E. A., and Feldman, J.: Computers and thought, McGraw–Hill, 1963.
Feldmann, R., Monien, B., Mysliwietz, P., and Vornberger, O.: ‘Distributed game tree search’, ICCA J.12 no. 2 (1989), 65–73.
Feldmann, R., Mysliwietz, P., and Monien, B.: ‘Game tree search on a massively parallel system’, in H. J. van den Herik, I. S. Herschberg, and J. W.H.M. Uiterwijk, (eds.): Advances in Computer Chess, Vol. 7 Univ. Limburg, 1994, pp. 203–218.
Finkel, R. A., and Fishburn, J. P.: ‘Parallelism in alpha-beta search’, Artif. Intell.19 (1982), 89–106.
Hewett, R., and Krishnamurthy, G.: ‘Consistent linear speedup in parallel alpha-beta search’, Proc. ICCI’92, Computing and Information, IEEE Computer Soc. Press, 1992, pp. 237–240.
Ibaraki, T.: ‘Generalization of alpha-beta and {SSS*} search procedures’, Artif. Intell.29 (1986), 73–117.
Karp, R. M., and Zhang, Y.: ‘On parallel evaluation of game trees’: ACM Annual Symp. Parallel Algorithms and Architectures (SPAA’89), ACM, 1989, pp. 409–420.
Knuth, D. E., and Moore, R. W.: ‘An analysis of alpha-beta pruning’, Artif. Intell., 6 no. 4 (1975), 293–326.
Marsland, T. A., and Campbell, M. S.: ‘Parallel search of strongly ordered game trees’, ACM Computing Surveys14 no. 4 (1982), 533–551.
Marsland, T. A., and Popowich, F.: ‘Parallel game-tree search’, IEEE Trans. Pattern Anal. Machine Intell. PAMI-7 no. 4 (July 1985), 442–452.
Marsland, T. A., Reinefeld, A., and Schaeffer, J.: ‘Low overhead alternatives to SSS∗’, Artif. Intell.31 (1987), 185–199.
McAllester, D. A.: ‘Conspiracy numbers for min-max searching’, Artif. Intell.35 (1988), 287–310.
Pearl, J.: ‘Asymptotical properties of minimax trees and game searching procedures’, Artif. Intell.14 no. 2 (1980), 113–138.
Pijls, W., and de Bruin, A.: ‘Another view of the SSS∗ algorithm’: Proc. Internat. Symp. (SIGAL’90), Aug. 1990.
Rivest, R. L.: ‘Game tree searching by min/max approximation’, Artif. Intell.34, no. 1 (1987), 77–96.
Roizen, I., and Pearl, J.: ‘A minimax algorithm better than alpha-beta? Yes and no’, Artif. Intell.21 (1983), 199–230.
Slagle, J. H., and Dixon, J. K.: ‘Experiments with some programs that search game trees’, J. ACM16 no. 2 (Apr. 1969), 189–207.
Steinberg, I. R., and Solomon, M.: ‘Searching game trees in parallel’, Proc. IEEE Internat. Conf. Parallel Processing, Vol. III, 1990, III–9–III–17.
Stockman, G. C.: ‘A minimax algorithm better than alpha-beta?’, Artif. Intell.12 no. 2 (1979), 179–196.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Kluwer Academic Publishers
About this entry
Cite this entry
Diderich, C.G., Gengler, M. (2001). Minimax Game Tree Searching . In: Floudas, C.A., Pardalos, P.M. (eds) Encyclopedia of Optimization. Springer, Boston, MA. https://doi.org/10.1007/0-306-48332-7_280
Download citation
DOI: https://doi.org/10.1007/0-306-48332-7_280
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-7923-6932-5
Online ISBN: 978-0-306-48332-5
eBook Packages: Springer Book Archive