Hostname: page-component-cb9f654ff-w5vf4 Total loading time: 0 Render date: 2025-08-07T13:08:28.121Z Has data issue: false hasContentIssue false

Computing preferred answer sets by meta-interpretation inAnswer Set Programming

Published online by Cambridge University Press:  31 July 2003

THOMAS EITER
Affiliation:
Institut für Informationssysteme 184/3, TU Wien Favoritenstr. 9-11, 1040 Wien, Austria (e-mail: eiter@kr.tuwien.ac.at)
WOLFGANG FABER
Affiliation:
Institut für Informationssysteme 184/3, TU Wien Favoritenstr. 9-11, 1040 Wien, Austria (e-mail: faber@kr.tuwien.ac.at)
NICOLA LEONE
Affiliation:
Department of Mathematics, University of Calabria 87030 Rende (CS), Italy (e-mail: leone@unical.it)
GERALD PFEIFER
Affiliation:
Institut für Informationssysteme 184/2, TU Wien Favoritenstr. 9-11, 1040 Wien, Austria (e-mail: pfeifer@dbai.tuwien.ac.at)

Abstract

Most recently, Answer Set Programming (ASP) has been attractinginterest as a new paradigm for problem solving. An important aspect,for which several approaches have been presented, is the handling ofpreferences between rules. In this paper, we consider the problem ofimplementing preference handling approaches by means ofmeta-interpreters in Answer Set Programming. In particular, weconsider the preferred answer set approaches by Brewka and Eiter, byDelgrande, Schaub and Tompits, and by Wang, Zhou and Lin. We presentsuitable meta-interpreters for these semantics using DLV, which isan efficient engine for ASP. Moreover, we also present ameta-interpreter for the weakly preferred answer set approach byBrewka and Eiter, which uses the weak constraint feature of DLV as atool for expressing and solving an underlying optimization problem.We also consider advanced meta-interpreters, which make use ofgraph-based characterizations and often allow for more efficientcomputations. Our approach shows the suitability of ASP in generaland of DLV in particular for fast prototyping. This can befruitfully exploited for experimenting with new languages andknowledge-representation formalisms.

Information

Type
Regular Papers
Copyright
© 2003 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

Footnotes

This paper is a revised and extended version of a preliminary paperin: Alessandro Provetti and Tran Cao Son, editors,Proceedings AAAI 2001 Spring Symposium on Answer SetProgramming: Towards Efficient and Scalable KnowledgeRepresentation and Reasoning, Stanford CA, March 2001,AAAI Press.