INDUCTION OF FIRST-ORDER DECISION LISTS - RESULTS ON LEARNING THE PAST TENSE OF ENGLISH VERBS

被引:52
作者
MOONEY, RJ
CALIFF, ME
机构
关键词
D O I
10.1613/jair.148
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
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).
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页码:1 / 24
页数:24
相关论文
共 40 条
[1]  
[Anonymous], 1983, ALGORITHMIC PROGRAM
[2]  
[Anonymous], 1986, MACHINE LEARNING ART
[3]  
BAIN M, 1992, INDUCTIVE LOGIC PROG, P423
[4]  
Bain Michael, 1992, INDUCTIVE LOGIC PROG, P145
[5]  
BERGADANO F, 1993, 13TH P INT JOINT C A, P1044
[6]   The Difficulties of Learning Logic Programs with Cut [J].
Bergadano, Francesco ;
Gunetti, Daniele ;
Trinchero, Umberto .
JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 1993, 1 :91-107
[7]  
CALIFF ME, 1994, UNPUB LEARNING PAST
[8]  
CAMERONJONES RM, 1994, SIGART B, V5, P33
[9]  
Clark P., 1989, Machine Learning, V3, P261, DOI 10.1023/A:1022641700528
[10]  
COHEN W, 1992, 9TH P INT C MACH LEA, P102