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Learning recursive theories with ATRE
D. Malerba,
F. Esposito,
and F. A. Lisi.
In H. Prade, editor, Proc. of the 13th European Conference on Artificial
Intelligence, pages 435--439. John Wiley \& Sons, August 1998.
Abstract
In this paper we present a new approach to the inductive inference of recursive
theories. A separate-and-parallel-conquer search strategy is adopted to
interleave the learning of clauses of mutually recursive predicate
definitions. Problems caused by the non-monotonicity of the consistency
property are solved by reformulating the currently learned theory before
adding a new clause. The proposedapproach is implemented in a new system,
named ATRE, which is characterized by an object-centered representation of
training examples and by the use of seed objects.
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