کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6895385 | 1445942 | 2018 | 36 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Jie Ke versus AlphaGo: A ranking approach using decision making method for large-scale data with incomplete information
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
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چکیده انگلیسی
Ranking historical players in sports is challenging since some players have never played against each other. It is even more complex in Go because of AlphaGo, a project based on artificial intelligence, who became the world's number 1 after it defeated the 528th and the 4th human Go players. AlphaGo is ranked high in the current Go ranking system because it is undefeated. The objective of this paper is to propose a new ranking method for large-scale Go players by means of incomplete fuzzy pair-wise comparison matrix whose priority vector is derived using a cosine similarity measure. Using match results provided by Go4Go.net, experiments are designed to rank top Go players in the past 45 years and examine the change in ranking after AlphaGo faced off against Jie Ke. Furthermore, the proposed method was applied to rank all 1544 Go players available at Go4Go.net to illustrate its efficiency in handling large-scale data.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Operational Research - Volume 265, Issue 1, 16 February 2018, Pages 239-247
Journal: European Journal of Operational Research - Volume 265, Issue 1, 16 February 2018, Pages 239-247
نویسندگان
Chao Xiangrui, Kou Gang, Li Tie, Peng Yi,