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CG
2008
Springer

Learning Positional Features for Annotating Chess Games: A Case Study

9 years 7 days ago
Learning Positional Features for Annotating Chess Games: A Case Study
Abstract. By developing an intelligent computer system that will provide commentary of chess moves in a comprehensible, user-friendly and instructive way, we are trying to use the power demonstrated by the current chess engines for tutoring chess and for annotating chess games. In this paper, we point out certain differences between the computer programs which are specialized for playing chess and our program which is aimed at providing quality commentary. Through a case study, we present an application of argument-based machine learning, which combines the techniques of machine learning and expert knowledge, to the construction of more complex positional features, in order to provide our annotating system with an ability to comment on various positional intricacies of positions in the game of chess.
Matej Guid, Martin Mozina, Jana Krivec, Aleksander
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where CG
Authors Matej Guid, Martin Mozina, Jana Krivec, Aleksander Sadikov, Ivan Bratko
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