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Representing Argumentation Frameworks in Answer Set Programming

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper studies representation of argumentation frameworks (AFs) in answer set programming (ASP). Four different transformations from AFs to logic programs are provided under the complete semantics, stable semantics, grounded semantics and preferred semantics. The proposed transformations encode labelling-based argumentation semantics in a simple manner, and different semantics of AFs are uniformly characterized by stable models of transformed programs. We apply transformed programs to solving AF problems such as query-answering, enforcement of arguments, agreement or equivalence of different AFs. Logic programming encodings of AFs are also used for representing assumption-based argumentation (ABA) in ASP. The results of this paper exploit new connections between argumentation theory and logic programming, and enable one to perform various argumentation tasks using existing answer set solvers.
Wydawca
Rocznik
Strony
261--292
Opis fizyczny
Bibliogr. 39 poz., rys., tab.
Twórcy
autor
  • Department of Computer and Communication Sciences, Wakayama University, Japan
autor
  • Interdisciplinary Centre for Security, Reliability and Trust University of Luxembourg, Luxembourg
Bibliografia
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  • [3] Baumann R, and Brewka G. Expanding argumentation frameworks: enforcing and monotonicity results. In: Proc. 3rd Int’l Conf. Computational Models of Argument. Frontiers in AI and Applications, IOS Press, 2010;216:75–86. ISBN:978-1-60750-618-8.
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  • [6] Brewka G, Eiter T, and Truszczyński M. Answer set programming at a glance. Communications of the ACM, 2011;54(12):92–103. doi:10.1145/2043174.2043195.
  • [7] Caminada M, and Gabbay D. A logical account of formal argumentation. Studia Logica, 2009;93:109–145. doi:10.1007/s11225-009-9218-x.
  • [8] Caminada M, Sá S, Alcântara J, and Dvořák W. On the equivalence between logic programming semantics and argumentation semantics. Journal of Approximate Reasoning, 2015;58:87–111. URL https://doi.org/10.1016/j.ijar.2014.12.004.
  • [9] Caminada M, Sá S, Alcântara J, and Dvořák W. On the difference between assumption-based argumentation and abstract argumentation. In: Proc. 25th Benelux Conf. Artificial Intelligence, 2013, p. 25–32. URL http://hdl.handle.net/2164/3148.
  • [10] Caminada M, and Schulz C. On the equivalence between assumption-based argumentation and logic programming. In: Proc. 1st Int’l Workshop on Argumentation and Logic Programming, Cork, Ireland, 2015.
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  • [14] Dung PM, Mancarella P, and Toni F. Computing ideal sceptical argumentation. Artificial Intelligence, 2007;171(10-15):642–674. URL https://doi.org/10.1016/j.artint.2007.05.003.
  • [15] Dung PM, Kowalski RA, and Toni F. Assumption-based argumentation. In: Argumentation in Artificial Intelligence (I. Rahwan and G. R. Simari, Eds.), Springer, 2009, p. 199–218. doi:10.1007/978-0-387-98197-0_10.
  • [16] Dunne PE, and Wooldridge M. Complexity of abstract argumentation. In: Argumentation in Artificial Intelligence (I. Rahwan and G. R. Simari, Eds.), Springer, 2009, p. 85–104. doi:10.1007/978-0-387-98197-0_5.
  • [17] Dvořák W, and Woltran S. On the intertranslatability of argumentation semantics. J. Artificial Intelligence Research 41, 2011, 445–475. URL http://dl.acm.org/citation.cfm?id=2051237.2051251.
  • [18] Dvořák W, Gaggl SA, Wallner JP, and Woltran S. Making use of advances in answer-set programming for abstract argumentation systems. In: Proc. 19th Int’l Conf. Applications of Declarative Programming and Knowledge Management, Revised Selected Papers, LNAI, vol. 7773, Springer, 2013, 114–133. doi: 10.1007/978-3-642-41524-1_7.
  • [19] Egly U, Gaggl SA, and Woltran S. Answer-set programming encodings for argumentation frameworks. Argument and Computation 2010;1(2):147–177. doi:10.1080/19462166.2010.486479.
  • [20] Gaggl SA, Manthey N, Ronca A, Wallner JP, and Woltran S. Improved answer-set programming encodings for abstract argumentation. Theory and Practice of Logic Programming, 2015;15:434–448. doi:10.1017/S1471068415000149.
  • [21] Gelfond M, and Lifschitz V. The stable model semantics for logic programming. In: Proc. 5th Int’l Conf. and Symp. Logic Programming, MIT Press, 1988, p. 1070–1080. URL http://www.cs.utexas.edu/users/ai-lab/?gel88.
  • [22] Gelfond M, and Lifschitz V. Classical negation in logic programs and disjunctive databases. New Generation Computing, 1991;9(3):365–385. doi:10.1007/BF03037169.
  • [23] Marquis SC, Konieczny S, Mailly JG, and Marquis P. Extension enforcement in abstract argumentation as an optimization problem. In: Proc. 24th Int’l Joint Conf. Artificial Intelligence, 2015, 2876–2882.
  • [24] Modgil S, and Caminada M. Proof theories and algorithms for abstract argumentation framework. In: Argumentation in Artificial Intelligence (I. Rahwan and G. R. Simari, Eds.), Springer, 2009, p. 105–129. doi:10.1007/978-0-387-98197-0_6.
  • [25] Nieves JC, Osorio M, and Cortés U. Preferred extensions as stable models. Theory and Practice of Logic Programming, 2008;8:527–543. URL https://doi.org/10.1017/S1471068408003359.
  • [26] Oikarinen E, and Janhunen T. Verifying the equivalence of logic programs in the disjunctive case. In: Proc. 7th Int’l Conf. Logic Programming and Nonmonotonic Reasoning, LNAI, vol. 2923, Springer, 2004, p. 180–193. doi:10.1007/978-3-540-24609-1_17.
  • [27] Oikarinen E, and Woltran S. Characterizing strong equivalence for argumentation frameworks. Artificial Intelligence, 2011;175(14-15):1985–2009. URL https://doi.org/10.1016/j.artint.2011.06.003.
  • [28] Prakken H. Combining sceptical epistemic reasoning with credulous practical reasoning (corrected version). Revised version of the paper originally published in: Proc. 1st Int’l Conf. Computational Models of Argument. Frontiers in AI and Applications 144, IOS Press, 2006, p. 311–322. ISBN:1-58603-652-1.
  • [29] Przymusinski TC. The well-founded semantics coincides with the three-valued stable semantics. Fundamenta Informaticae, 1990;13(4):445–463. URL http://dl.acm.org/citation.cfm?id=107720.107722.
  • [30] Sakama C. Dishonest arguments in debate games. In: Proc. 4th Int’l Conf. Computational Models of Argument. Frontiers in AI and Applications, IOS Press, 2012;245(1):177–184. doi:10.3233/978-1-61499-111-3-177.
  • [31] Schlipf J. Complexity and undecidability results for logic programming. Annals of Mathematics and Artificial Intelligence, 1995;15(3):257–288. doi:10.1007/BF01536398.
  • [32] Schulz C, and Toni F. Complete assumption labellings. In: Proc. 5th Int’l Conf. Computational Models of Argument. Frontiers in AI and Applications, IOS Press, 2014;266:405–412. doi:10.3233/978-1-61499-436-7-405.
  • [33] Schulz C. Assumption labellings. Technical Report, Imperial College, London, UK, 2015.
  • [34] Toni F, and Sergot M. Argumentation and answer set programming. In: Logic Programming, Knowledge Representation, and Nonmonotonic Reasoning: Essays in Honor of Michael Gelfond (M. Balduccini and T. C. Son, Eds.), LNCS, vol. 6565, Springer, 2011, p. 164–180. doi:10.1007/978-3-642-20832-4_11.
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  • [36] Wakaki T, and Nitta K. Computing argumentation semantics in answer set programming. New Frontiers in Artificial Intelligence (H. Hattori et al:, Eds.), LNAI, vol. 5447, Springer, 2009, p. 254–269. doi:10.1007/978-3-642-00609-8_22.
  • [37] Wallner JP, Niskanen A, and Jarvisalo M. Complexity results and algorithms for extension enforcement in abstract argumentation. In: Proc. 30th AAAI Conf. Artificial Intelligence, 2016, p. 1088–1094.
  • [38] Wu Y, Caminada M, and Gabbay DM. Complete extensions in argumentation coincide with 3-valued stable models in logic programming. Studia Logica, 2009;93(2-3):383–403. URL http://www.jstor.org/stable/40587173.
  • [39] You JH, and Yuan LY. A three-valued semantics for deductive databases and logic programs. J. Computer and System Science, 1994;49(2):334–361. URL https://doi.org/10.1016/S0022-0000(05)80053-4.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0c7313f0-ccb9-4fd5-aa68-f8c53942b67d
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