DOGMA: A GA-Based Relational Learner

Jukka Hekanaho

Turku Centre for Computer Science
and
Abo Akademi University
Department of Computer Science
Lemminkisenkatu 14 A, SF-20520 Turku, Finland
hekanaho@abo.fi



Abstract. We describe a GA-based concept learning/theory revision
system DOGMA and discuss how it can be applied to relational learning.
The search for better theories in DOGMA is guided by a novel fitness
function that combines the minimal description length and information
gain measures. To show the efficacy of the system we compare it to other
learners in two relational domains.
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