著者

岡山 将也 真野 芳久 村本 正生

出版者

社団法人人工知能学会

雑誌

人工知能学会誌 (ISSN:09128085)

巻号頁・発行日

vol.11, no.1, pp.86-95, 1996-01-01

被引用文献数

1

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Consider the situation that an analogical reasoning model is investigated considering the practical application, it is necessary to consider the effective knowledge retrieval to solve given problems. In most of the analogical reasoning models which have been proposed, knowledge is retrieved with some criteria from knowledge base, and problems are solved by using of the retrieved and/or general knowledge. However, these models were using the search and combination of all the elements in the knowledge base, impricitly. So, the knowledge retrieval often becomes explosively complex. In our method at first one problem is divided into several sub-problems, then they are analized individually with appropriate knowledge base and the results are harmonized to solve. As the sub-problems can refer several different knowledge base, the combination of the targets will not be complicated. Thus it is not necessary to deal with the large targets all at once and the retrieval time is reduced. In this paper, we propose analogical reasoning model based on knowledge classification. Further-more, we applied the pilot system to the domain of mathematical problems such as equation problems. By using this system, we compared the time during problem solving with our model to the time without ours, and show the efficiency of our model.