Abstract
There are two types of formalization for induction in logic. In descriptive induction, induced hypotheses describe rules with respect to observations with all predicates minimized. In explanatory induction, on the other hand, hypotheses abductively account for observations without any minimization principle. Both inductive methods have strength and weakness, which are complementary to each other. In this work, we unify these two logical approaches. In the proposed framework, not all predicates are minimized but minimality conditions can be flexibly determined as a circumscription policy. Constructing appropriate policies, we can intentionally minimize models of an augmented axiom set. As a result, induced hypotheses can have both conservativeness and explainability, which have been considered incompatible with each other in the literature. We also give two procedures to compute inductive hypotheses in the proposed framework.
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Inoue, K., Saito, H. (2004). Circumscription Policies for Induction. In: Camacho, R., King, R., Srinivasan, A. (eds) Inductive Logic Programming. ILP 2004. Lecture Notes in Computer Science(), vol 3194. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30109-7_15
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DOI: https://doi.org/10.1007/978-3-540-30109-7_15
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