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Plausible Move Generation Using Move Merit Analysis with Cut-Off Thresholds in Shogi

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Computers and Games (CG 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2063))

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Abstract

In games where the number of legal moves is too high, it is not possible to do full-width search to a depth sufficient for good play. Plausible move generation (PMG) is an important search alternative in such domains. In this paper we propose a new method for plausible move generation in shogi. During move generation, Move Merit Analysis (MMA) gives a value to each move based on the plausible move generator(s) that generated the move. These values can be used for different cut-off schemes. We investigate the following alternatives: 1) Keep all moves with a positive MMA value; 2) Order the moves according to their MMA value and use cut-off thresholds to keep the best N moves. PMG with MMA and cut-off thresholds can save between 46% and 68% of the total number of legal moves with an accuracy between 99% and 93%. Tests show that all versions of shogi programs using PMG with MMA outperform an equivalent shogi program using full-width search. It is also shown that MMA is vital for our approach. Plausible move generation with MMA performs much better than plausible move generation without MMA. Cut-off thresholds improve the performance for N = 20 or N = 30.

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Author information

Authors and Affiliations

  1. Department of Information Science, Saga University, 1 Honjo-machi, Saga-shi, Saga-ken, Japan, 840-8502

    Reijer Grimbergen

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  1. Reijer Grimbergen
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Alberta, Edmonton, Alberta, Canada

    Tony Marsland

  2. Future University - Hakodate, Hakodate, Hokkaido, Japan

    Ian Frank

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© 2001 Springer-Verlag Berlin Heidelberg

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Grimbergen, R. (2001). Plausible Move Generation Using Move Merit Analysis with Cut-Off Thresholds in Shogi. In: Marsland, T., Frank, I. (eds) Computers and Games. CG 2000. Lecture Notes in Computer Science, vol 2063. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45579-5_21

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  • DOI: https://doi.org/10.1007/3-540-45579-5_21

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43080-3

  • Online ISBN: 978-3-540-45579-0

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