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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
Current issue: Feb 2018
Next issue: May 2018
Avg review time: 107 days


Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

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  3/2009 - 17

Modelling Imprecise Arguments in Description Logic

LETIA, I.A. See more information about LETIA, I.A. on SCOPUS See more information about LETIA, I.A. on IEEExplore See more information about LETIA, I.A. on Web of Science, GROZA, A. See more information about GROZA, A. on SCOPUS See more information about GROZA, A. on SCOPUS See more information about GROZA, A. on Web of Science
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Download PDF pdficon (123 KB) | Citation | Downloads: 922 | Views: 4,081

Author keywords
semi-structured argumentation, description logic, fuzzy logic

References keywords
logic(8), argumentation(8), intelligence(6), fuzzy(6), arguments(6), systems(4), reed(4), reasoning(4), hunter(4), chris(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2009-10-26
Volume 9, Issue 3, Year 2009, On page(s): 94 - 99
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2009.03017
Web of Science Accession Number: 000271872000017
SCOPUS ID: 77954784217

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Real arguments are a mixture of fuzzy linguistic variables and ontological knowledge. This paper focuses on modelling imprecise arguments in order to obtain a better interleaving of human and software agents argumentation, which might be proved useful for extending the number of real life argumentative-based applications. We propose Fuzzy Description Logic as the adequate technical instrumentation for filling the gap between human arguments and software agents arguments. A proof of concept scenario has been tested with the fuzzyDL reasoner.

References | Cited By  «-- Click to see who has cited this paper

[1] Fernando Bobillo and Umberto Straccia, "fuzzyDL: An expressive fuzzy description logic reasoner", 2008 International Conference on Fuzzy Systems (FUZZ-08), pp. 923-930, IEEE Computer Society, 2008
[CrossRef] [Web of Science Times Cited 82] [SCOPUS Times Cited 183]

[2] P. Dunne, A. Hunter, P. McBurney, S. Parsons, M. Wooldridge, "Inconsistency Tolerance in Weighted Argument Systems", Proceedings of the Eighth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'09), ACM Press

[3] Guido Governatori, Michael J. Maher, Grigoris Antoniou, and David Billington. Argumentation semantics for defeasible logic. Journal of Logic and Comput, 14(5):675-702, 2004
[CrossRef] [Web of Science Times Cited 105] [SCOPUS Times Cited 144]

[4] Anthony Hunter, "Real arguments are approximate arguments", AAAI, pp. 66-71. AAAI Press, 2007

[5] Dirk Vermeir Jeroen Janssen and Martine De Cock, "Fuzzy argumentation frameworks", IPMU, pp. 513-520, 2008

[6] Joel Katzav and Chris Reed, "On argumentation schemes and the natural classification of arguments. Argumentation", 18(2):239-259, 2004
[CrossRef] [SCOPUS Times Cited 30]

[7] Franz Baader, Diego Calvanese, Deborah McGuinness, Danielle Nardi, and Peter Patel-Schneider, "The Description Logic Handbook", Cambridge University Press, 2003

[8] John L. Pollock, "Defeasible reasoning with variable degrees of justification", Artif. Intell., 133(1-2):233-282, 2001
[CrossRef] [Web of Science Times Cited 68] [SCOPUS Times Cited 90]

[9] Henry Prakken, "A study of actual of arguments, with applications to evidential reasoning", International Conference on Artificial Intelligence and Law, pp. 85-94. ACM, 2005
[CrossRef] [SCOPUS Times Cited 75]

[10] Iyad Rahwan and Bita Banihashemi, "Arguments in OWL: A progress report", Philippe Besnard, Sylvie Doutre, and Anthony Hunter, editors, COMMA, volume 172 of Frontiers in Artificial Intelligence and Applications, pp. 297-310. IOSPress, 2008

[11] Iyad Rahwan, Fouad Zablith, and Chris Reed, "Laying the foundations for a World Wide Argument Web", Artif. Intell., 171(10-15):897-921, 2007

[12] Chris Reed and Glenn Rowe, "Araucaria: Software for argument analysis, diagramming and representation", International Journal on Artificial Intelligence Tools, 13(4), 2004

[13] Douglas Walton, "Fundamentals of Critical Argumentation", Cambridge University Press, 2006
[CrossRef] [Web of Science Times Cited 132] [SCOPUS Times Cited 163]

[14] Paul Krause, Simon Ambler, Morten Elvang Goransson, and John Fox, "A Logic of Argumentation for Reasoning under Uncertainty", Computational Intelligence:11, pp. 113-131, 1995
[CrossRef] [Web of Science Times Cited 42] [SCOPUS Times Cited 63]

[15] Teresa Alsinet, Carlos I. Chesnevar, Lluis Godo, Guillermo Simari, "A Logic Programming Framework for Possibilistic Argumentation: Formalising and Logical Properties", Fuzzy Sets and Systems (FSS) 159(10):1208-1228, 2008

[16] Philippe Besnard and Anthony Hunter, "Practical First-Order Argumentation", AAAI, 2005, pp 590-595, 2005

[17] P. M. Dung, "On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games", Artificial Intelligence, 77:321-357, 1995
[CrossRef] [Web of Science Times Cited 1392] [SCOPUS Times Cited 2098]

[18] Umberto Straccia, "A Fuzzy Description Logic for the Semantic Web", Capturing Intelligence, Elie Sanchez ed., Elsevier, 73:90, 2006
[CrossRef] [Web of Science Times Cited 99] [SCOPUS Times Cited 153]

[19] Carlos Ivan Chesnevar, Jarred McGinnis, Sanjay Modgil, Iyad Rahwan, Chris Reed, Guillermo Ricardo Simari, Matthew South, Gerard Vreeswijk, Steven Willmott, "Towards an argument interchange format", Knowledge Eng. Review 21(4): 293-316, 2006
[CrossRef] [Web of Science Times Cited 99] [SCOPUS Times Cited 153]

References Weight

Web of Science® Citations for all references: 2,019 TCR
SCOPUS® Citations for all references: 3,152 TCR

Web of Science® Average Citations per reference: 106 ACR
SCOPUS® Average Citations per reference: 166 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2018-03-23 01:52 in 85 seconds.

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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania

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