A Quantitative Analysis of Minimal Window Search

Use of minimal windows enhances the aB algorithm in practical applications as well as in the search of artificially constructed game trees. Nevertheless, there exists no theoretical model to measure the strengths and weaknesses of minimal window search. In particular, it is not known which tree ordering properties are favorable for minimal window search. This paper presents a quantitative analysis of minimal window search based on recursive equations which assess the influence of static node values on the dynamic search process. The analytical model is computationally simple, easily extendible and gives a realistic estimate of the expected search time for averagely ordered game trees. 1 In t roduc t ion

[1]  Rajjan Shinghal,et al.  An empirical comparison of pruning strategies in game trees , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[2]  John Philip Fishburn.  Analysis of speedup in distributed algorithms , 1984 .

[3]  Judea Pearl,et al.  Asymptotic Properties of Minimax Trees and Game-Searching Procedures , 1980, Artif. Intell..

[4]  Fred Popowich,et al.  Parallel Game-Tree Search , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Alexander Reinefeld,et al.  An Improvement to the Scout Tree Search Algorithm , 1983, J. Int. Comput. Games Assoc..

[6]  T. Anthony Marsland,et al.  A Comparison of Minimax Tree Search Algorithms , 1983, Artif. Intell..

[7]  Donald E. Knuth,et al.  The Solution for the Branching Factor of the Alpha-Beta Pruning Algorithm , 1981, ICALP.