Learning Three-Valued Logic Programs

We show that the adoption of a three-valued setting for inductive concept learning is particularly useful for learning. Distinguishing between what is true, what is false and what is unknown can be useful in situations where decisions have to be taken on the basis of scarce information. In order to learn in a three-valued setting, we adopt Extended Logic Programs (ELP) under a Well-Founded Semantics with explicit negation (WFSX ) as the representation formalism for learning. Standard Inductive Logic Programming techniques are then employed to learn the concept and its opposite. The learnt de nitions of the positive and negative concepts may overlap. In the paper, we handle the issue of combination of possibly contradictory learnt de nitions, and we show strategies for theory re nement.

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