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The principal continuation and the killer heuristic

Published: 01 January 1977 Publication History

Abstract

An algorithm is presented for obtaining the principal continuation in trees searched by two-person game playing programs based on the Alpha-Beta algorithm. Moves saved while determining the principal continuation are shown to be good candidates for killer moves when the killer heuristic supplements the Alpha-Beta search.

References

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J. von Neumann, "Zur Theorie der Gesellshaftsspiele", Math. Annalen, vol. 100, 1928, pp. 295-320.
[2]
C.E. Shannon, "Programming a computer for playing chess", Philosophical Magazine, ser. 7, vol. 41, No. 314, March 1950, pp. 256-275.
[3]
A.M. Turing, "Faster than thought", B.V. Bowden ed., London, Pitman, 1953, Chap. 25, pp. 288-295.
[4]
A. Bertstein and M. Roberts, "Computer v. Chess-Player", Scientific American, June 1958, pp. 96-105.
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A. Newell, J.C. Shaw and H.A. Simon, "Chess playing programs and the problem of complexity", IBM J. Res. and Devel., 2, 1958, pp. 320 - 355.
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A. Samuel, "Some studies in machine learning using the game of checkers", IBM J. Res. and Devel., 3, 1959, pp. 211 - 229.
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A. Brudno, "Bounds and valuations for shortening and scanning of variations", in Russian, Problemy Kibernetiki, 10, 1963, pp. 141-150.
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A. Samuel, "Some studies in machine learning using the game of checkers II - Recent Progress", IBM J. Res. and Devel., 11, 1967, pp. 601-617.
[9]
J.R. Slagle and J.K. Dixon, "Experiments with some programs that search game trees", J. ACM, 16, 1969, pp. 189-207.
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J.J. Gillogly, "The technology chess program", Artificial Intelligence, 3, 1972, pp. 145-163.
[11]
D.E. Knuth, "An Analysis of alpha-beta pruning", Department of Computer Science Report, Stanford University, STAN CS-74-441, 64 pages, August 1974.
[12]
M.M. Newborn, "The Efficiency of the Alpha-Beta search on trees with branch-dependent terminal node scores", Artificial Intelligence, Vol. 8, pp. 137-153, 1977.
[13]
M.M. Newborn, "PEASANT: An endgame program for Kings and Pawns", Chess Skill in Man and Machine, Frey, P., Ed., Springer Verlag, pp. 119-130, 1977.
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N. Nilsson, Problem Solving Methods in Artificial Intelligence, McGraw-Hill, 1971.
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M.M. Newborn, Computer Chess, Academic Press, 1975.

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cover image ACM Conferences
ACM '77: Proceedings of the 1977 annual conference
January 1977
505 pages
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 January 1977

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October 16 - 19, 1977
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  • (2021)Adaptive Relaxations for Multistage Robust OptimizationPRICAI 2021: Trends in Artificial Intelligence10.1007/978-3-030-89188-6_36(485-499)Online publication date: 25-Oct-2021
  • (2020)Guiding Multiplayer MCTS by Focusing on Yourself2020 IEEE Conference on Games (CoG)10.1109/CoG47356.2020.9231603(550-557)Online publication date: Aug-2020
  • (2020)A Novel Application for Game Tree Search - Exploiting Pruning Mechanisms for Quantified Integer ProgramsAdvances in Computer Games10.1007/978-3-030-65883-0_6(66-78)Online publication date: 20-Dec-2020
  • (2019)Design and implementation of military chess game algorithm based on probability model and situation evaluation2019 Chinese Control And Decision Conference (CCDC)10.1109/CCDC.2019.8832525(6310-6314)Online publication date: Jun-2019
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  • (2016)Challenging Established Move Ordering Strategies with Adaptive Data StructuresTrends in Applied Knowledge-Based Systems and Data Science10.1007/978-3-319-42007-3_73(862-872)Online publication date: 14-Jul-2016
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