Evolutionary Search in Inductive Equational Logic Programming

Concept learning is the induction of a description from a set of examples. Inductive logic programming can be considered a special case of the general notion of concept learning specifically referring to the induction of first-order theories. Both concept learning and inductive logic programming can be seen as a search over all possible sentences in some representation language for sentences that correctly explain the examples and also generalize to other sentences that are part of that concept. In this paper we explore inductive logic programming with equational logic as the representation language. We present a high-level overview of the implementation of inductive equational logic using genetic programming and discuss encouraging results based on experiments that are intended to emulate real world scenarios.