First Order Theory Refinement

Abstract

. This paper summarizes the current state of the art in the topics of first-order theory revision and theory restructuring. The various tasks involved in first-order theory refinement (revision vs. restructuring) are defined and then discussed in turn. For theory revision, the issue of minimality is discussed in detail, and a general outline algorithm is given which identifies the major places of difference between different algorithms. The paper then describes the various options that have been explored by different researchers. For theory restructuring, two approaches developed in the ILP project are discussed, one devoted to understandability, and the other devoted to efficiency. First-order methods of inductive learning have witnessed considerable interest in recent years, and the field of Inductive Logic Programming (ILP) [26] has developed rapidly. While the original ILP learning task deals with learning first-order clausal theories from scratch given examples and background kno...