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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/19704

Title: Factor Analyses on Positive and Negative Evaluations of Games against Go Programs
Authors: Kuboki, Kyota
Hsueh, Chu-Hsuan
Ikeda, Kokolo
Keywords: Evaluation factor analysis
Player preference
The game of Go
Issue Date: 2024-03-28
Publisher: Springer, Singapore
Magazine name: 28th International Conference on Technologies and Applications of Artificial Intelligence (TAAI 2023)
Start page: 343
End page: 357
DOI: 10.1007/978-981-97-1711-8_26
Abstract: Analyzing users’ preferences is important for many platforms to further improve users’ satisfaction or make recommendations. This is the same for online game platforms. In this paper, we target a classical board game, the game of Go, and investigate the factors that make human players feel enjoyable when playing against Go programs on a website. In addition, we also investigate whether different players feel enjoyable in different ways. We use game records collected from the website, where players can evaluate games as enjoyable or not. We conduct statistical analyses using basic information, such as game lengths or players’ win rates, as well as advanced analyses using information extracted by a strong Go program, such as the qualities of moves. The results show that some factors are generally common among players, while some factors show completely opposite preferences. For example, players generally prefer opponents with proper playing skills; meanwhile, some prefer close games and some prefer to win by large margins.
Rights: This is the author's version of the work. Copyright (C) 2024 Kyota Kuboki, Chu-Hsuan Hsueh, and Kokolo Ikeda, under exclusive license to Springer Nature Singapore Pte Ltd. The version published by Springer, Singapore is available at https://doi.org/10.1007/978-981-97-1711-8_26
URI: http://hdl.handle.net/10119/19704
Material Type: author
Appears in Collections:d11-1. 会議発表論文 (Conference Papers)

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