MATHEMATICAL MODELING AND ANALYSIS TO DETERMINE A SHOGI PLAYER’S SKILL LEVEL
https://doi.org/10.34822/1999-7604-2022-3-14-24
Abstract
The study deals with obtaining numerical estimates of shogi pieces’ disposition on the board with the help of software. Using these estimates, the authors intend to evaluate a player’s skill. That requires collecting data, reviewing and repeating existing approaches, proposing and implementing the authors’ approach, and comparing the results. The difference in strength of two players is calculated based on their win distribution via resimulation of the Ferreira approach. In implementing Yamashita’s approach, the relation between Elo rating and the average degradation of the position estimate as a result of a bad move is searched for. The authors’ approach is proposed to estimate a player’s skill. Hence, the dependence of wins, good and bad moves, the deviation of the estimates of real and ideal moves, and the average improvement of the position from the Elo rating are analyzed. The study attempts to cluster plays and moves.
About the Authors
O. P. Bobrovskaya
Surgut State University, Surgut
Russian Federation
Russian Federation
Master’s Degree Student
E-mail: o-bobrovskaya@mail.ru
S. V. Lysenkova
Surgut State University, Surgut
Russian Federation
Russian Federation
Candidate of Sciences (Physics and Mathematics)
E-mail: lysenkova_sa@surgu.ru
References
1. Drezewski R., Wątor G. Chess as Sequential Data in a Chess Match Outcome Prediction Using Deep Learning with Various Chessboard Representations // Procedia Computer Science. 2021. Vol. 192. P. 1760–1769.
2. Guid M., Bratko I. Computer Analysis of World Chess Champions // ICGA Journal. 2006. Vol. 29, № 2. P. 65–73.
3. Regan K. W., Haworth G. M. Intrinsic Chess Ratings // Proceedings of the AAAI Conference on Artificial Intelligence. 2011. Vol. 25, № 1. P. 834–839.
4. Alliot J.-M. Who is the Master? // ICGA Journal. 2017. Vol. 39, № 1. P. 3–43.
5. Ferreira D. R. Determining the Strength of Chess Players Based on Actual Play // ICGA Journal. 2012. Vol. 35, № 1. P. 3–19.
6. Yamashita H. Pro Shogi Players Rating and Game Record Analysis // Proceedings of the Game Programming Workshop. 2014. P. 9–16.
7. Takatsu K., Takada H., Hirata T. How to Estimate the Rating of the Youngest Professional Shogi Player Souta Fujii // Memoir of Graduate School of Engineering, University of Fukui. 2019. Vol. 67. P. 1–9.
8. Christ M., Braun N., Neuffer J., Kempa-Liehr A. W. Time Series FeatuRe Extraction on Basis of Scalable Hypothesis Tests (Tsfresh – A Python Package) // Neurocomputing. 2018. Vol. 307. P. 72–77. URL: https://www.sciencedirect.com/science/article/pii/S0925231218304843 (дата обращения: 23.05.2022).
9. Umargono E., Suseno J. E., Gunawan S. K. V. K-Means Clustering Optimization Using the Elbow Method and Early Centroid Determination Based on Mean and Median Formula // Proceedings of the 2nd International Seminar on Science and Technology (ISSTEC 2019). 2020. P. 121–129. URL: https://www.researchgate.net/publication/346349075_K-Means_Clustering_Optimization_Using_the_Elbow_Method_and_Early_Centroid_Determination_Based_ on_Mean_and_Median_Formula (дата обращения: 29.05.2022).
10. De Amorim R. C., Hennig C. Recovering the Number of Clusters in Data Sets with Noise Features Using Feature Rescaling Factors // Information Sciences. 2015. Vol. 324. P. 126–145. URL: https://arxiv.org/ pdf/1602.06989.pdf (дата обращения: 29.05.2022).
11. Shi C., Wei B., Wei S. et al. A Quantitative Discriminant Method of Elbow Point for the Optimal Number of Clusters in Clustering Algorithm // J Wireless Com Network. 2021. P. 31. DOI 10.1186/ s13638-021-01910-w (дата обращения: 29.05.2022).
Review
For citations:
Bobrovskaya O.P., Lysenkova S.V. MATHEMATICAL MODELING AND ANALYSIS TO DETERMINE A SHOGI PLAYER’S SKILL LEVEL. Proceedings in Cybernetics. 2022;(3 (47)):14-24. (In Russ.) https://doi.org/10.34822/1999-7604-2022-3-14-24
Views:
130
Email this article 