UnissResearch

Logo Universitàegli studi di Sassari
titoli, abstracts, parole chiave >>>
Multi-engine ASP solving with policy adaptation

Maratea, Marco and Pulina, Luca and Ricca, Francesco (08 October 2012) Multi-engine ASP solving with policy adaptation. Alghero, University of Sassari - Computer Vision Laboratory. p. 24 (CVL 2012/004). Technical Report.

[img]
Preview
Full text disponibile come PDF Richiede visualizzatore di PDF come GSview, Xpdf o Adobe Acrobat Reader
825Kb

Abstract

The recent application of Machine Learning techniques to the Answer Set Programming (ASP) field proved to be effective. In particular, the multi-engine ASP solver ME-ASP is efficient: it is able to solve more instances than any other ASP system that participated to the 3rd ASP Competition on the "System Track" benchmarks. In the ME-ASP approach, classification methods inductively learn off-line algorithm selection policies starting from both a set of features of instances in a training set, and the solvers performance on such instances.
In this paper we present an improvement to the multi-engine framework of ME-ASP, in which we add the capability of updating the learned policies when the original approach fails to give good predictions. An experimental analysis, conducted on training and test sets of ground instances obtained from the ones submitted to the "System Track" of the 3rd ASP Competition, shows that the policy adaptation improves the performance of ME-ASP when applied to test sets containing domains of instances that were not considered for training.

Item Type:Technical Report
ID Code:8017
Status:Submitted
Uncontrolled Keywords:Answer Set Programming (ASP), ASP solving, applying machine learning techniques
Subjects:Area 09 - Ingegneria industriale e dell'informazione > ING-INF/05 Sistemi di elaborazione delle informazioni
Divisions:001 Università di Sassari > 01-a Nuovi Dipartimenti dal 2012 > Scienze Politiche, Scienze della Comunicazione e Ingegneria dell'Informazione
001 Università di Sassari > 02 Centri > Computer Vision Laboratory
Publisher:University of Sassari - Computer Vision Laboratory
Deposited On:06 Nov 2012 13:57

I documenti depositati in UnissResearch sono protetti dalle leggi che regolano il diritto d'autore

Repository Staff Only: item control page