Inductive Logic Programming (ILP) is one of the new and fast growing sub-fields of artificial intelligence. Given a specification language, the goal is to induce a logic program from examples of how the program should work (and also of how it should not work). One main difficulty of ILP lies in learning recursively defined predicates. Today's systems strongly rely on a set of supporting predicates known as the background knowledge that helps define the recursive clause. The dependence on background knowledge has its drawbacks in that it is assumed that the user knows in advance what sort of predicates are required by the target definition. Predicate invention, a research topic that has received a lot of attention lately, can remedy the situation by extending the specification language with new concepts, which appear neither in the examples nor in the background knowledge, and finding a definition for them. A serious concern is that no examples of the invented predicate are explicitly given but rather of the target predicate, so learning has to be done in the absence or scarcity of examples. This research is concerned with the problem of learning recursive definitions based on inverting clausal implication from a small data set. The aim is both to derive an autonomous learning method that can invent the recursive predicates it needs, and to implement it in an efficient manner. Experiments show that the system is capable of finding a correct definition of many relations by inventing the necessary predicates, but does not perform very well on random examples. A comparison between several similar systems that learn recursive definitions of a single predicate is shown. We also show the need for system-generated negative examples and discuss several pitfalls of predicate invention and the absence/scarcity of examples.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/4271 |
| Date | January 1998 |
| Creators | Rios, Riverson. |
| Contributors | Matwin, S., |
| Publisher | University of Ottawa (Canada) |
| Source Sets | Université d’Ottawa |
| Detected Language | English |
| Type | Thesis |
| Format | 197 p. |
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