Integrating induction and abduction in logic programming

作     者：Lamma, E Mello, P Milano, M Riguzzi, F 

作者机构：Univ Bologna DEIS I-40136 Bologna Italy 

出 版 物：《INFORMATION SCIENCES》 (信息科学)

年 卷 期：1999年第116卷第1期

页      面：25-54页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：MURST 

主　　题：abductive logic programming inductive logic programming machine learning nonmonotonic reasoning 

摘      要：We propose an approach for the integration of abduction and induction in Logic Programming. We define an Abductive Learning Problem as an extended Inductive Logic Programming problem where both the background and target theories are abductive theories and where abductive derivability is used as the coverage relation instead of deductive derivability. The two main benefits of this integration are the possibility of learning in presence of incomplete knowledge and the increased expressive power of the background and target theories. We present the system LAP (Learning Abductive Programs) that is able to solve this extended learning problem and we describe, by means of examples, four different learning tasks that can be performed by the system: learning from incomplete knowledge, learning rules with exceptions, learning from integrity constraints and learning recursive predicates. (C) 1999 Elsevier Science Inc. All rights reserved.