Algorithmic approaches to modeling and analyzing endgame positions in backgammon
DOI:
https://doi.org/10.17721/1812-5409.2026/1.27Keywords:
backgammon, "races" stage, probability theory, total probability formula, simulation, optimal strategies, doubling cube, pip-count, game optimizationAbstract
The final phase of the backgammon game, known as "races", is considered. This phase is characterized by minimizing the interaction of opponent's checkers and reducing the game process mainly to assessing the rate of moving checkers to the "home" and their subsequent withdrawal from the board. The delivered analysis covers the specifics of this stage in various backgammon variants, in particular in classic backgammon, using mathematical models and probability theory. The paper proposes methods for optimizing strategies in the final phase of the game, which are based on a comprehensive analysis of possible game positions and calculating the probabilities of the dices values. Special attention is paid to algorithmic approaches to decision-making, which allow calculating the most effective game actions to achieve the optimal result.
The results of the study are valuable both for improving the game strategies of practicing players and beginners, and for developing theoretical approaches to game analysis based on modeling and assessing the effectiveness of decision-making in conditions of limited interaction between participants.
Pages of the article in the issue: 206 - 212
Language of the article: English
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Copyright (c) 2026 Serhii Dotsenko, Georgi Dimitrov, Anastasiya Vecherkovskaya, Igor Makushenko
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