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Evaluating Go Game Records for Prediction of Player Attributes
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SYSNO ASEP 0459376 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Evaluating Go Game Records for Prediction of Player Attributes Author(s) Moudřík, J. (CZ)
Baudiš, P. (CZ)
Neruda, Roman (UIVT-O) SAI, RID, ORCIDSource Title Proceedings of the 2015 IEEE Conference on Computational Intelligence and Games. - Piscataway : IEEE, 2015 - ISSN 2325-4289 - ISBN 978-1-4799-8622-4 Pages s. 162-168 Number of pages 7 s. Publication form Online - E Action CIG 2015. IEEE Conference on Computational Intelligence and Games Event date 31.08.2015 - 05.09.2015 VEvent location Tainan Country TW - Taiwan, Province of China Event type WRD Language eng - English Country US - United States Keywords computer Go ; machine learning ; feature extraction ; board games ; skill assessment Subject RIV IN - Informatics, Computer Science R&D Projects GA15-19877S GA ČR - Czech Science Foundation (CSF) Institutional support UIVT-O - RVO:67985807 UT WOS 000376490300017 EID SCOPUS 84964452603 DOI 10.1109/CIG.2015.7317909 Annotation We propose a way of extracting and aggregating permove evaluations from sets of Go game records. The evaluations capture different aspects of the games such as played patterns or statistic of sente/gote sequences. Using machine learning algorithms, the evaluations can be utilized to predict different relevant target variables. We apply this methodology to predict the strength and playing style of the player (e.g. territoriality or aggressivity) with good accuracy. We propose a number of possible applications including aiding in Go study, seeding realwork ranks of internet players or tuning of Go-playing programs. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2017
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