Title: Learning a Tsume-Go heuristic with Tilde
Authors: Ramon, Jan ×
Francis, Tom
Blockeel, Hendrik #
Issue Date: 2001
Publisher: Springer
Host Document: Lecture notes in computer science vol:2063 pages:151-169
Conference: Second international Conference on Computers and Games location:Hamamatsu, Japan date:October 26-28, 2000
Abstract: In Go, an important factor that hinders search is the large branching factor, even in local problems. Human players are strong at recognizing frequently occurring shapes and vital points. This allows them to select the most promising moves and to prune the search tree. In this paper we argue that many of these shapes can be represented as relational concepts. We present an application of the relational learner TILDE in which we learn a heuristic that gives values to candidate-moves in tsume-go (life and death) problems. Such a heuristic can be used to limit the number of evaluated moves. Even if all moves are evaluated, alpha-beta search can be sped up considerably when the candidate-moves are approximately ordered from good to bad.We validate our approach with experiments and analysis.
ISSN: 0302-9743
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Informatics Section
× corresponding author
# (joint) last author

Files in This Item:
File Status SizeFormat
32254.pdf Published 158KbAdobe PDFView/Open


All items in Lirias are protected by copyright, with all rights reserved.