文章基本信息

标题：Offspring Generation Method for interactive Genetic Algorithm considering Multimodal Preference
本地全文：下载
作者：Fuyuko Ito ; Tomoyuki Hiroyasu ; Mitsunori Miki 等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2009
卷号：24
期号：1
页码：127-135
DOI：10.1527/tjsai.24.127
出版社：The Japanese Society for Artificial Intelligence
摘要：In interactive genetic algorithms (iGAs), computer simulations prepare design candidates that are then evaluated by the user. Therefore, iGA can predict a user's preferences. Conventional iGA problems involve a search for a single optimum solution, and iGA were developed to find this single optimum. On the other hand, our target problems have several peaks in a function and there are small differences among these peaks. For such problems, it is better to show all the peaks to the user. Product recommendation in shopping sites on the web is one example of such problems. Several types of preference trend should be prepared for users in shopping sites. Exploitation and exploration are important mechanisms in GA search. To perform effective exploitation, the offspring generation method (crossover) is very important. Here, we introduced a new offspring generation method for iGA in multimodal problems. In the proposed method, individuals are clustered into subgroups and offspring are generated in each group. The proposed method was applied to an experimental iGA system to examine its effectiveness. In the experimental iGA system, users can decide on preferable t-shirts to buy. The results of the subjective experiment confirmed that the proposed method enables offspring generation with consideration of multimodal preferences, and the proposed mechanism was also shown not to adversely affect the performance of preference prediction.
关键词：interactive genetic algorithms ; offspring generation ; clustering ; preference ; multimodality