Integrating induction and abduction in logic programming

We propose an approach for the integration of abduction and induction in Lo gic Programming. We define an Abductive Learning Problem as an extended Ind uctive Logic Programming problem where both the background and target theor ies 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 incomple te knowledge and the increased expressive power of the background and targe t 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, learn ing from integrity constraints and learning recursive predicates. (C) 1999 Elsevier Science Inc. All rights reserved.