ILP: A Short Look Back and a Longer Look Forward

David Page, Ashwin Srinivasan; 4(Aug):415-430, 2003.


Inductive logic programming (ILP) is built on a foundation laid by research in machine learning and computational logic. Armed with this strong foundation, ILP has been applied to important and interesting problems in the life sciences, engineering and the arts. This paper begins by briefly reviewing some example applications, in order to illustrate the benefits of ILP. In turn, the applications have brought into focus the need for more research into specific topics. We enumerate and elaborate five of these: (1) novel search methods; (2) incorporation of explicit probabilities; (3) incorporation of special-purpose reasoners; (4) parallel execution using commodity components; and (5) enhanced human interaction. It is our hypothesis that progress in each of these areas can greatly improve the contributions that can be made with ILP; and that, with assistance from research workers in other areas, significant progress in each of these areas is possible.