文章基本信息

标题：Induction of First-Order Decision Lists: Results on Learning the Past Tense of English Verbs
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作者：R. J. Mooney ; M. E. Califf
期刊名称：Journal of Artificial Intelligence Research
印刷版ISSN：1076-9757
出版年度：1995
卷号：3
页码：1-24
出版社：American Association of Artificial
摘要：This paper presents a method for inducing logic programs from examples that learns a new class of concepts called first-order decision lists, defined as ordered lists of clauses each ending in a cut. The method, called FOIDL, is based on FOIL (Quinlan, 1990) but employs intensional background knowledge and avoids the need for explicit negative examples. It is particularly useful for problems that involve rules with specific exceptions, such as learning the past-tense of English verbs, a task widely studied in the context of the symbolic/connectionist debate. FOIDL is able to learn concise, accurate programs for this problem from significantly fewer examples than previous methods (both connectionist and symbolic).