著者

千葉 和也 大和田 勇人 溝口 文雄

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.16, no.1, pp.156-163, 2001 (Released:2002-02-28)

参考文献数

15

被引用文献数

1 2 1

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In this paper, we apply Inductive Logic Programming (ILP) to acquire graphic design knowledge. Acquiring design knowledge is a challenging task because such knowledge is complex and vast. We thus focus on principles of layout and constraints that layouts must satisfy to realize automatic layout generation. Although we do not have negative examples in this case, we can generate them randomly by considering that a page with just one element moved is always wrong. Our nonmonotonic learning method introduces a new predicate for exceptions. In our method, the ILP algorithm is executed twice, exchanging positive and negative examples. From our experiments using magazine advertisements, we obtained rules characterizing good layouts and containing relationships between elements. Moreover, the experiments show that our method can learn more accurate rules than normal ILP can.