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.
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Notes
- 1.
No-contact positions where a player has pinned the 1-point (also known as “mana” point) are proven double wins for the pinning player except for the rare cases when the opponent has also pinned the 1-point (tie).
- 2.
For brevity, ‘he’ and ‘his’ whenever ‘he or she’ and ‘his or her’ are meant.
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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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Papahristou, N., Refanidis, I. (2015). Constructing Pin Endgame Databases for the Backgammon Variant Plakoto. In: Plaat, A., van den Herik, J., Kosters, W. (eds) Advances in Computer Games. ACG 2015. Lecture Notes in Computer Science(), vol 9525. Springer, Cham. https://doi.org/10.1007/978-3-319-27992-3_16
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