On the Computation of Paracoherent Answer Sets

Giovanni Amendola; Carmine Dorado; Wolfgang Faber; Nicola Leone; Francesco Ricca

On the Computation of Paracoherent Answer Sets

Giovanni Amendola, Carmine Dorado, Wolfgang Faber, Nicola Leone, Francesco Ricca

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Answer Set Programming (ASP) is a well-established formalism for nonmonotonic reasoning. An ASP program can have no answer set due to cyclic default negation. In this case, it is not possible to draw any conclusion, even if this is not intended. Recently, several paracoherent semantics have been proposed that address this issue,and several potential applications for these semantics have been identified. However, paracoherent semantics have essentially been inapplicable in practice, due to the lack of efficient algorithms and implementations. In this paper, this lack is addressed, and several different algorithms to compute semi-stable and semi-equilibrium models are proposed and implemented into an answer set solving framework. An empirical performance comparison among the new algorithms on benchmarks from ASP competitions is given as well.

Original language	English
Title of host publication	Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence
Subtitle of host publication	(AAAAI-17)
Editors	Satinder Singh, Shaul Markovitch
Publisher	AAAI press
Pages	1034-1040
Number of pages	7
Volume	1
ISBN (Print)	1577357809, 9781577357803
Publication status	Published - 1 Jul 2017
Event	31st Association for the Advancement of Artificial Intelligence Conference on Artificial Intelligence - Hilton San Francisco Union Square, San Francisco, United States Duration: 4 Feb 2017 → 9 Feb 2017 Conference number: 31 https://aaai.org/ocs/index.php/AAAI/AAAI17/index (Link to Conference Details)

Conference

Conference	31st Association for the Advancement of Artificial Intelligence Conference on Artificial Intelligence
Abbreviated title	AAAI-17
Country/Territory	United States
City	San Francisco
Period	4/02/17 → 9/02/17
Internet address	https://aaai.org/ocs/index.php/AAAI/AAAI17/index (Link to Conference Details)

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https://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14358Licence: Unspecified

Cite this

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title = "On the Computation of Paracoherent Answer Sets",

abstract = "Answer Set Programming (ASP) is a well-established formalism for nonmonotonic reasoning. An ASP program can have no answer set due to cyclic default negation. In this case, it is not possible to draw any conclusion, even if this is not intended. Recently, several paracoherent semantics have been proposed that address this issue,and several potential applications for these semantics have been identified. However, paracoherent semantics have essentially been inapplicable in practice, due to the lack of efficient algorithms and implementations. In this paper, this lack is addressed, and several different algorithms to compute semi-stable and semi-equilibrium models are proposed and implemented into an answer set solving framework. An empirical performance comparison among the new algorithms on benchmarks from ASP competitions is given as well.",

keywords = "Answer Set Programming, Paracoherent Answer Set, Inconsistency Tolerance, Nonmonotonic Reasoning",

author = "Giovanni Amendola and Carmine Dorado and Wolfgang Faber and Nicola Leone and Francesco Ricca",

note = "Publisher will not allow accepted version to be viewable via repository. Also cannot find ISBN or ISSN. HN 11/10/2017; 31st Association for the Advancement of Artificial Intelligence Conference on Artificial Intelligence, AAAI-17 ; Conference date: 04-02-2017 Through 09-02-2017",

year = "2017",

month = jul,

day = "1",

language = "English",

isbn = "1577357809",

volume = "1",

pages = "1034--1040",

editor = "Satinder Singh and Shaul Markovitch",

booktitle = "Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence",

publisher = "AAAI press",

address = "United States",

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Amendola, G, Dorado, C, Faber, W, Leone, N & Ricca, F 2017, On the Computation of Paracoherent Answer Sets. in S Singh & S Markovitch (eds), Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence: (AAAAI-17). vol. 1, AAAI press, pp. 1034-1040, 31st Association for the Advancement of Artificial Intelligence Conference on Artificial Intelligence, San Francisco, California, United States, 4/02/17. <http://eprints.hud.ac.uk/id/eprint/32167/>

On the Computation of Paracoherent Answer Sets. / Amendola, Giovanni; Dorado, Carmine; Faber, Wolfgang et al.

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence: (AAAAI-17). ed. / Satinder Singh; Shaul Markovitch. Vol. 1 AAAI press, 2017. p. 1034-1040.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - On the Computation of Paracoherent Answer Sets

AU - Amendola, Giovanni

AU - Dorado, Carmine

AU - Faber, Wolfgang

AU - Leone, Nicola

AU - Ricca, Francesco

N1 - Conference code: 31

PY - 2017/7/1

Y1 - 2017/7/1

N2 - Answer Set Programming (ASP) is a well-established formalism for nonmonotonic reasoning. An ASP program can have no answer set due to cyclic default negation. In this case, it is not possible to draw any conclusion, even if this is not intended. Recently, several paracoherent semantics have been proposed that address this issue,and several potential applications for these semantics have been identified. However, paracoherent semantics have essentially been inapplicable in practice, due to the lack of efficient algorithms and implementations. In this paper, this lack is addressed, and several different algorithms to compute semi-stable and semi-equilibrium models are proposed and implemented into an answer set solving framework. An empirical performance comparison among the new algorithms on benchmarks from ASP competitions is given as well.

AB - Answer Set Programming (ASP) is a well-established formalism for nonmonotonic reasoning. An ASP program can have no answer set due to cyclic default negation. In this case, it is not possible to draw any conclusion, even if this is not intended. Recently, several paracoherent semantics have been proposed that address this issue,and several potential applications for these semantics have been identified. However, paracoherent semantics have essentially been inapplicable in practice, due to the lack of efficient algorithms and implementations. In this paper, this lack is addressed, and several different algorithms to compute semi-stable and semi-equilibrium models are proposed and implemented into an answer set solving framework. An empirical performance comparison among the new algorithms on benchmarks from ASP competitions is given as well.

KW - Answer Set Programming

KW - Paracoherent Answer Set

KW - Inconsistency Tolerance

KW - Nonmonotonic Reasoning

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M3 - Conference contribution

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SN - 9781577357803

VL - 1

SP - 1034

EP - 1040

BT - Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence

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A2 - Markovitch, Shaul

PB - AAAI press

T2 - 31st Association for the Advancement of Artificial Intelligence Conference on Artificial Intelligence

Y2 - 4 February 2017 through 9 February 2017

ER -

On the Computation of Paracoherent Answer Sets

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