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The Multi-Engine ASP Solver me-asp

  • Marco Maratea
  • Luca Pulina
  • Francesco Ricca
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7519)

Abstract

In this paper we describe the new system me-asp, which applies machine learning techniques for inductively choosing, among a set of available ones, the “best” ASP solver on a per-instance basis. Moreover, we report the results of some experiments, carried out on benchmarks from the “System Track” of the 3rd ASP Competition, showing the state-of-the-art performance of our solver.

Keywords

System Track Logic Program Inductive Model Disjunctive Database Apply Machine Learning Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Marco Maratea
    • 1
  • Luca Pulina
    • 2
  • Francesco Ricca
    • 3
  1. 1.DIBRISUniv. degli Studi di GenovaGenovaItaly
  2. 2.POLCOMINGUniv. degli Studi di SassariSassariItaly
  3. 3.Dipartimento di MatematicaUniv. della CalabriaRendeItaly

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