Creation of Training Data and Training for Prediction Model of Curling Scores Using Real Game Data

Tomoya Iwasaki, Wataru Noguchi, Yasumasa Tamura, Shimpei Aihara, Masahito Yamamoto

2024

Abstract

Curling is a sport in which two teams take turns shoting stones at each other on an ice field to compete for total scores. Curling is a highly strategic sport, and the strategy of stone delivering has a significant impact on the outcome of the game. To verify strategy of curling, “digital curling” is a platform that reproduces curling on a computer. Following the previous research of curling AI using game tree search and evaluation function by Ataka et al., real game data was obtained and trained into a neural network of evaluation function. In this study, we propose a method to obtain stone position information from real game data. Also, the model was trained from the obtained data. The results show that models trained with realistic data correspond better to realistic situations than conventional models trained with data generated by algorithms. However, in situations where there are many stones on the sheet, the model was also found to be insufficiently accurate as is the case with conventional models.

Paper Citation

in Harvard Style

Iwasaki T., Noguchi W., Tamura Y., Aihara S. and Yamamoto M. (2024). Creation of Training Data and Training for Prediction Model of Curling Scores Using Real Game Data. In Proceedings of the 12th International Conference on Sport Sciences Research and Technology Support - Volume 1: icSPORTS; ISBN 978-989-758-719-1, SciTePress, pages 168-179. DOI: 10.5220/0012941100003828

in Bibtex Style

@conference{icsports24,
author={Tomoya Iwasaki and Wataru Noguchi and Yasumasa Tamura and Shimpei Aihara and Masahito Yamamoto},
title={Creation of Training Data and Training for Prediction Model of Curling Scores Using Real Game Data},
booktitle={Proceedings of the 12th International Conference on Sport Sciences Research and Technology Support - Volume 1: icSPORTS},
year={2024},
pages={168-179},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012941100003828},
isbn={978-989-758-719-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Sport Sciences Research and Technology Support - Volume 1: icSPORTS
TI - Creation of Training Data and Training for Prediction Model of Curling Scores Using Real Game Data
SN - 978-989-758-719-1
AU - Iwasaki T.
AU - Noguchi W.
AU - Tamura Y.
AU - Aihara S.
AU - Yamamoto M.
PY - 2024
SP - 168
EP - 179
DO - 10.5220/0012941100003828
PB - SciTePress