NDLI: M-eval: A Multivariate Evaluation Function for Opening Positions in Computer Go

Content Provider	IEEE Xplore Digital Library
Author	Basaldúa, J. Tai-Ning Yang Marcos Moreno Vega, J.
Copyright Year	2010
Abstract	Recently, computer go has experienced great advance with the introduction of Monte-Carlo Tree Search (MCTS). Although MCTS programs are overall stronger than previous programs, their strength manifests mostly as the game advances. Strong human players applying established opening principles overtake current MCTS programs in the early moves of nonhandicap 19x19 games. In this paper, the authors propose a method, M-eval, for implementing these opening principles in a program. M-eval is a multivariate evaluation function that provides a priori information for MCTS-based go programs. An initial vector made of k positive qualities both players wish to maximize is computed on a board position for each player. The initial vector is dimensionally reduced using non-negative matrix factorization to minimize informational loss. This reduction is done using the multivariate structure learned offline from a set of over 110,000 board positions from a database of master human games. The resulting R2 encoding is converted by regression to a real value used as a priori information in MCTS. Games were played using the MCTS GoKnot/QYZ framework with M-eval enabled against the same program without M-eval. Results show valuable improvement both in territorial gain and number of wins.
Starting Page	474
Ending Page	480
File Size	289195
Page Count	7
File Format	PDF
ISBN	9781424486687
DOI	10.1109/TAAI.2010.80
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-18
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Computers Shape Non-negative matrix factorization Computer go Humans Encoding Multivariate analysis Positional judgment Databases Monte-Carlo tree search Games Machine learning
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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