Externally Supported Models for Efficient Computation of Paracoherent Answer Sets

Giovanni Amendola, Carmine Dodaro, Wolfgang Faber, Francesco Ricca

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

Answer Set Programming (ASP) is a well established formalism for nonmonotonic reasoning. While incoherence, the non-existence of answer sets for some programs, is an important feature of ASP, it has frequently been criticised and indeed has some disadvantages, especially for query answering. Paracoherent semantics have been suggested as a remedy, which extend the classical notion of answer sets to draw meaningful conclusions also from incoherent programs. In this paper we present an alternative characterization of the two major paracoherent semantics in terms of (extended) externally supported models. This definition uses a transformation of ASP programs that is more parsimonious than the classic epistemic transformation used in recent implementations. A performance comparison carried out on benchmarks from ASP competitions shows that the usage of the new transformation brings about performance improvements that are independent of the underlying algorithms.
Original languageEnglish
Title of host publicationProceedings of the Thirty-Second AAAI Conference on Artificial Intelligence
EditorsSheila McIlraith, Kilian Weinberger
PublisherAAAI press
Number of pages8
Publication statusPublished - 25 Apr 2018
Event32nd Association for the Advancement of Artificial Intelligence Conference - Hilton New Orleans Riverside, New Orleans, United States
Duration: 2 Feb 20187 Feb 2018
Conference number: 32
https://aaai.org/Conferences/AAAI-18/ (Link to Conference Details)

Conference

Conference32nd Association for the Advancement of Artificial Intelligence Conference
Abbreviated titleAAAI-18
CountryUnited States
CityNew Orleans
Period2/02/187/02/18
Internet address

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Cite this

Amendola, G., Dodaro, C., Faber, W., & Ricca, F. (2018). Externally Supported Models for Efficient Computation of Paracoherent Answer Sets. In S. McIlraith, & K. Weinberger (Eds.), Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence AAAI press.