%0 Conference Proceedings
%T Generating the Expression of the Move of Go by Classifier Learning
%+ Université de Tsukuba = University of Tsukuba
%A Mori, Natsumi
%A Utsuro, Takehito
%Z Part 7: Game Design
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 16th International Conference on Entertainment Computing (ICEC)
%C Tsukuba City, Japan
%Y Nagisa Munekata
%Y Itsuki Kunita
%Y Junichi Hoshino
%I Springer International Publishing
%3 Entertainment Computing – ICEC 2017
%V LNCS-10507
%P 299-309
%8 2017-09-18
%D 2017
%R 10.1007/978-3-319-66715-7_33
%K Entertainment computing
%K Go
%K Classifier learning
%K Move
%K Expression
%Z Computer Science [cs]Conference papers
%X The ancient Chinese board game, Go, with its simple rules yet highly complex strategies, requires players to encircle more territory than their opponent. However, owing to the rise in the capabilities of Go-playing software and a lack of Go instructors in Japan, there is a need for a software that actively assists human players in learning the high-level strategies required to win the game. This study focuses on generating a review for each consecutive player’s move. This paper studies how to generate an expression for each move based on the distribution of the stones on the board. To this task of generating the expression for each move in a game of Go, we apply a classifier learning technique.
%G English
%Z TC 14
%2 https://inria.hal.science/hal-01771268/document
%2 https://inria.hal.science/hal-01771268/file/978-3-319-66715-7_33_Chapter.pdf
%L hal-01771268
%U https://inria.hal.science/hal-01771268
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-ICEC
%~ IFIP-TC14
%~ IFIP-LNCS-10507