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Constructing Pin Endgame Databases for the Backgammon Variant Plakoto

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Part of the Lecture Notes in Computer Science book series (LNCS, volume 9525)

Abstract

Palamedes is an ongoing project for building expert playing bots that can play backgammon variants. Until recently the position evaluation relied only on self-trained neural networks. This paper describes the first attempt to augment Palamedes by constructing databases for certain endgame positions for the backgammon variant of Plakoto. The result is 5 databases containing 12,480,720 records in total; they can calculate accurately the best move for roughly 3.4 × 1015 positions. To the best of our knowledge, this is the first time that an endgame database is created for this game.

Keywords

Endgame Databases Backgammon Endgame Positions Palamedes Game Theoretical Value 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgements

The authors would like to thank the anonymous referees for their useful comments and suggestions that contributed to improving the final version of the paper.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.University of MacedoniaThessalonikiGreece

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