A Model+Solver Approach to Concept Learning

  • Francesca Alessandra Lisi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10037)


Many Concept Learning problems can be seen as Constraint Satisfaction Problems (CSP). In this paper, we propose a model+solver approach to Concept Learning which combines the efficacy of Description Logics (DLs) in conceptual modeling with the efficiency of Answer Set Programming (ASP) solvers in dealing with CSPs.


Concept learning Declarative modeling Description logics Answer set programming Constraint satisfaction 



We would like to thank the proposers of the bounded model semantics for the fruitful discussions about their work during a visit to Dresden and for the kind remote assistance in using Wolpertinger.


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© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Dipartimento di InformaticaUniversità degli Studi di Bari “Aldo Moro”BariItaly

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