The tutorial will provide a complete survey of "Logic and Learning" and will concentrate on learning in first order logic. Early research involved structural matching, least general generalization, model inference, and theory restructuring. Recently, the area of logic and learning has concentrated on Inductive Logic Programming, which studies inductive machine learning within the representation of logic programming.
The course gives an overview of the history, techniques and applications
of logic and learning. Logical and algorithmic foundations of this field
are emphasized, and illustrated by means of well-known systems and
algorithms. This includes: learning as search, logical representations,
operators and settings for induction, state-of-the-art methods and
systems, and applications in knowledge discovery and logic
programming. For use in data mining and knowledge discovery, pointers to
the available public domain systems are provided and discussed.
The course assumes basic knowledge of artificial intelligence and logic
(e.g. some notions about Prolog and/or the predicate calculus).
About the Lecturers
is a research associate at the J. Stefan Institute, Ljubljana
(Slovenia). Her main research interest is in inductive logic programming
and medical applications of machine learning. She is co-author and
editor of several books published by Sigma Press, MIT Press, Kluwer and
Springer, including "Inductive Logic Programming: Techniques and
Applications" (Ellis Horwood 1994). She was a coordinator of ILPNET, the
European Scientific Network in Inductive Logic Programming (1993-96).
Luc De Raedt is a post-doctoral researcher and a (part-time) assistant professor at the Katholieke Universiteit Leuven (Belgium). His main interest is in inductive logic programming. He is a coordinator of the European ESPRIT III and IV projects on Inductive Logic Programming, was chair of the ILP-95 workshop, and he has published two books on inductive logic programming. He has given tutorials and invited talks on ILP at ISMIS-93, ILPS-93, MSL-96, LOPSTR 96, etc.