ESPRIT III Basic Research Action ILP
Project description
Basic Research Action #6020 investigates Inductive Logic Programming (ILP), the intersection of inductive learning and logic programming.
The project will address theoretical issues and implementation of prototype learners and will carry out empirical evaluations.
It is being financed for the duration of three years, starting
on September 1, 1992.
Approach and Methods
The project focusses on the following research topics :
- Theory of ILP
- the theoretical implications of the use of logic programming
for inductive learners; this involves the study of :
- the properties of generalisation and specialisation operators
such as inverse resolution
- the complexity and convergence aspects of particular inductive
- algorithms (this is concerned with learnability theory)
- logical frameworks for induction
- the development of a framework and methodology for empirical evaluation
of ILP-learners
- Theory Revision
- the issues involved in learning multiple concepts in
a first order logic framework; learning multiple concepts
is a form of theory revision, where several related predicates or
concepts may be modified or revised.
- Imperfect data
- to upgrade and adapt
existing noise-handling mechanisms from attribute value learning algorithms.
- Predicate Invention
- the investigation of methods to invent new predicates; these methods aim at extending the vocabulary
of the learner whenever the available vocabulary is unsatisfactory
or insufficient
and by doing so they extend the range of learnable concepts.
- Declarative Bias
- the exploration of methods and formalisms
to explicitly and declaratively represent the bias
of inductive logic learners.
Aims
The main long term technical goal of the ILP project
is to upgrade the techniques of the classical empirical learning paradigm
to a logic programming framework.
In this way ILP aims to overcome the two main limitations
of classical empirical or similarity based learning algorithms, such
as the TDIDD-family :
- the use of a limited knowledge representation formalism (essentially a propositional logic), and
- the inability to use substantial background knowledge in the learning process.
Partners
Coordinator
Katholieke Universiteit Leuven, Belgium
Partners
Gesellschaft fur Mathematik und Datenverarbeitung, Germany
Universitat Stuttgart, Germany
CNRS - LRI, France
Universita di Torino, Italy
University of Oxford, United Kingdom
Associate Partner
University of Stockholm, Sweden
Subcontractors
Jozef Stefan Institute, Slovenia
Attila Jozsef University, Hungary
Katholieke Universiteit Brabant, Netherlands
University of Dortmund, Germany