Title: Iterative versionspaces with an application in inductive logic programming
Authors: Sablon, Gunther
Issue Date: May-1995
Series Title: pages:278
Abstract: This thesis consists of two parts: in the first part we develop a
language-independent framework for efficiently solving concept
learning problems; in the second part we apply this framework to
Inductive Logic Programming.

We view concept learning as a search problem. In the well-known
framework of Versionspaces a bi-directional depth-first search
algorithm that learns a maximally general and maximally specific
concept representation is presented, and contrasted to the
breadth-first approach of Mellish's Description Identification
algorithm. In this context, we identify redundant information
elements, in order to reduce the memory needed for storing information
elements. We describe how automatically generated information elements
can replace less informative ones.

Next, we extend this framework to describe the more complex
versionspaces that originate from introducing disjunctions. To be
practically useful, we gradually restrict these disjunctive
versionspaces by imposing preference criteria, based on notions of
minimality. This leads to extensions of the non-disjunctive algorithms
to the disjunctive case.

In the second part of the thesis we show in detail how this general
framework can be instantiated to Inductive Logic Programming. In this
respect we also discuss the integration of machine learning in a
planning system based on Horn clause logic. This illustrates that the
use of a logical representation allows a smooth integration of Machine
Learning and Problem Solving.

In summary, the thesis contributes to the understanding and the
development of search algorithms for concept learning in general, by
developing a language independent framework, and by introducing
several novel and generally applicable concept learning
techniques. The application in the second part of the thesis shows
that the framework is practically useful, and that it contributes to
the field of Inductive Logic Programming.
Publication status: published
KU Leuven publication type: TH
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