A tutorial on assumption-based argumentation

REFERENCES

• Amgoud, L., & Prade, H. (2009). Using arguments for making and explaining decisions. Artificial Intelligence, 173, 413–436. doi: 10.1016/j.artint.2008.11.006
   Web of Science ®Google Scholar
• Besnard, P., & Hunter, A. (2008). Elements of argumentation. Cambridge, MA: MIT Press.
   Google Scholar
• Bondarenko, A., Dung, P.M., Kowalski, R.A., & Toni, F. (1997). An abstract, argumentation-theoretic approach to default reasoning. Artificial Intelligence, 93, 63–101. doi: 10.1016/S0004-3702(97)00015-5
   Web of Science ®Google Scholar
• Bondarenko, A., Toni, F., & Kowalski, R.A. (1993). An assumption-based framework for non-monotonic reasoning. In L.M. Pereira & A. Nerode Eds.), Proceedings of the 2nd international workshop on logic programming and non-monotonic reasoning (LPNMR 1993), June (pp. 171–189). Lisbon, Portugal: MIT Press.
   Google Scholar
• Brewka, G. (1989). Preferred subtheories: An extended logical framework for default reasoning. In Proc. IJCAI (pp. 1043–1048), San Francisco, CA: Morgan Kaufmann.
   Google Scholar
• Caminada, M., & Amgoud, L. (2007). On the evaluation of argumentation formalisms. Artificial Intelligence, 171, 286–310. doi: 10.1016/j.artint.2007.02.003
   Web of Science ®Google Scholar
• Cayrol, C., Devred, C., & Lagasquie-Schiex, M.C. (2006). Handling controversial arguments in bipolar argumentation systems. In P.E. Dunne & T.J.M. Bench-Capon (Eds.), Computational models of argument: Proceedings of COMMA 2006, September 11–12, 2006, Liverpool, UK, Volume 144, Frontiers in artificial intelligence and applications (pp. 261–272). Amsterdam, he Netherlands: IOS Press.
   Google Scholar
• Craven, R., Toni, F., Hadad, A., Cadar, C., & Williams, M. (2012). Efficient support for medical argumentation. In G. Brewka, T. Eiter & S.A. McIlraith (Eds.), Proc. 13th international conference on principles of knowledge representation and reasoning (pp. 598–602). Palo Alto, CA: AAAI Press.
   Google Scholar
• Craven, R., Toni, F., & Williams, M. (2013). Graph-based dispute derivations in assumption-based argumentation. In E. Black, S. Modgil, & N. Oren (Eds.), Theories and applications of formal argumentation – second international workshop, TAFA 2013, Lecture Notes in Artificial Intelligence, Springer, to appear.
   Google Scholar
• Dimopoulos, Y., Nebel, B., & Toni, F. (2002). On the computational complexity of assumption-based argumentation for default reasoning. Artificial Intelligence, 141, 57–78. doi: 10.1016/S0004-3702(02)00245-X
   Web of Science ®Google Scholar
• Dung, P.M. (1991). Negations as hypotheses: An abductive foundation for logic programming. In Proceedings of the international conference in logic programming, pp. 3–17, Cambridge, MA: MIT Press.
   Google Scholar
• Dung, P.M. (1995). On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence, 77, 321–358. doi: 10.1016/0004-3702(94)00041-X
   Web of Science ®Google Scholar
• Dung, P.M., Kowalski, R.A., & Toni, F. (2006). Dialectic proof procedures for assumption-based, admissible argumentation. Artificial Intelligence, 170, 114–159. doi: 10.1016/j.artint.2005.07.002
   Web of Science ®Google Scholar
• Dung, P.M., Kowalski, R.A., & Toni, F. (2009). Assumption-based argumentation. In I. Rahwan and G. Simari (Eds.), Argumentation in AI (pp. 199–218). Berlin, Germany: Springer.
   Google Scholar
• Dung, P.M., Mancarella, P., & Toni, F. (2007). Computing ideal sceptical argumentation. Artificial Intelligence, Special Issue on Argumentation in Artificial Intelligence, 171, 642–674.
   Web of Science ®Google Scholar
• Dung, P.M., & Thang, P.M. (2010). Towards (probabilistic) argumentation for jury-based dispute resolution. In P. Baroni, F. Cerutti, M. Giacomin, & G.R. Simari (Eds.), Computational models of argument: Proceedings of COMMA 2010, Desenzano del Garda, Italy, September 8-10, 2010, Vol. 216 of Frontiers in Artificial Intelligence and Applications (pp. 171–182). Amsterdam, he Netherlands: IOS Press.
   Google Scholar
• Dung, P.M., Toni, F., & Mancarella, P. (2010). Some design guidelines for practical argumentation systems. In P. Baroni, F. Cerutti, M. Giacomin and G. Simari (Eds.), Proceedings of the Third International Conference on Computational Models of Argument (COMMA’10) (Vol. 216, pp. 183–194). IOS Press,
   Google Scholar
• Dunne, P.E. (2009). The computational complexity of ideal semantics. Artificial Intelligence, 173, 1559–1591. doi: 10.1016/j.artint.2009.09.001
   Web of Science ®Google Scholar
• Elvang-Gøransson, M., & Hunter, A. (1995). Argumentative logics: Reasoning with classically inconsistent information. Data & Knowledge Engineering, 16, 125–145. doi: 10.1016/0169-023X(95)00013-I
   Web of Science ®Google Scholar
• Eshghi, K., & Kowalski, R.A. (1989). Abduction compared with negation by failure. In ICLP, pp. 234–254, Cambridge, MA: MIT Press.
   Google Scholar
• Fan, X., Craven, R., Singer, R., Toni, F., & Williams, M. (2013). Assumption-based argumentation for decision-making with preferences: A medical case study. In J. Leite, T.C. Son, P. Torroni, L. van der Torre, & S. Woltran (Eds.), Computational logic in multi-agent systems – 14th international workshop, CLIMA XIV, Corunna, Spain, September 16–18. Lecture Notes in Artificial Intelligence, ol. 8143. Berlin, Germany: Springer.
   Google Scholar
• Fan, X., & Toni, F. (2011). Assumption-based argumentation dialogues. In T. Walsh (Ed.), IJCAI 2011, proceedings of the 22nd international joint conference on artificial Intelligence (pp. 198–203). Palo Alto, CA: IJCAI/AAAI.
   Google Scholar
• Fan, X., & Toni, F. (2012). Agent strategies for aba-based information-seeking and inquiry dialogues. In L.D. Raedt, C. Bessière, D. Dubois, P. Doherty, P. Frasconi, F. Heintz, & P.J.F. Lucas (Eds.), Proceedings of 20th European conference on artificial intelligence (ECAI 2012), Vol. 242 of Frontiers in artificial intelligence and a Applications (pp. 324–329). Amsterdam, he Netherlands: IOS Press.
   Google Scholar
• Fan, X., & Toni, F. (2013). Decision making with assumption-based argumentation. In E. Black, S. Modgil, & N. Oren (Eds.), Theories and applications of formal argumentation – second international workshop, TAFA 2013, Lecture Notes in Artificial Intelligence, Springer, to appear.
   Google Scholar
• Gaertner, D., & Toni, F. (2007). On computing arguments and attacks in assumption-based argumentation. IEEE Intelligent Systems, Special Issue on Argumentation Technology, 22, 24–33.
   Web of Science ®Google Scholar
• García, A.J., & Simari, G.R. (2004). Defeasible logic programming: An argumentative approach. Theory and Practice of Logic Programming, 4, 95–138. doi: 10.1017/S1471068403001674
   Web of Science ®Google Scholar
• Gelfond, M. (2007). Answer sets. In F. van Harmelen, V. Lifschitz, & B. Parter (Eds.), Handbook of knowledge representation ( Chapter 7, pp. 285–316). New York City, USA: Elsevier.
   Google Scholar
• Kakas, A.C., Kowalski, R.A., & Toni, F. (1992). Abductive logic programming. Journal of Logic and Computation, 2, 719–770. doi: 10.1093/logcom/2.6.719
   Google Scholar
• Kakas, A.C., Kowalski, R.A., & Toni, F. (1998). The role of abduction in logic programming. In D.M. Gabbay, C.J. Hogger, & J.A. Robinson (Eds.), Handbook of logic in artificial intelligence and logic programming (pp. 235–324). Oxford: Oxford University Press.
   Google Scholar
• Kakas, A.C., Mancarella, P., Sadri, F., Stathis, K., & Toni, F. (2008). Computational logic foundations of KGP agents. Journal of Artificial Intelligence Research, 33, 285–348.
   Web of Science ®Google Scholar
• Kakas, A.C., & Toni, F. (1999). Computing negation as failure via argumentation. Journal of Logic and Computation, 9, 515–562. doi: 10.1093/logcom/9.4.515
   Web of Science ®Google Scholar
• Kowalski, R.A., & Sadri, F. (1999). From logic programming towards multi-agent systems. Annals of Mathematics in Artificial Intelligence, 25, 391–419. doi: 10.1023/A:1018934223383
   Web of Science ®Google Scholar
• Kowalski, R.A., & Toni, F. (1996). Abstract argumentation. Artificial Intelligence and Law, 4, 275–296 (also published in ‘Logical Models of Argumentation’). doi: 10.1007/BF00118494
   Google Scholar
• Krause, P., Ambler, S., Elvang-Gøransson, M., & Fox, J. (1995). A logic of argumentation for reasoning under uncertainty. Computational Intelligence, 11, 113–131. doi: 10.1111/j.1467-8640.1995.tb00025.x
   Web of Science ®Google Scholar
• Krause, P., Ambler, S., & Fox, J. (1992). The development of a ‘logic of argumentation’. In B. Bouchon-Meunier, L. Valverde, & R.R. Yager (Eds.), IPMU ’92 – advanced methods in artificial intelligence, proceedings of the 4th international conference on processing and management of uncertainty in knowledge-based systems, Vol. 682 of Lecture notes in computer science (pp. 109–118). Berlin, Germany: Springer.
   Google Scholar
• Lin, F., & Shoham, Y. (1989). Argument systems: A uniform basis for nonmonotonic reasoning. In R.J. Brachman, H.J. Levesque, & R. Reiter (Eds.), Proceedings of the 1st international conference on principles of knowledge representation and reasoning (KR’89). Toronto, Canada, May 15–18 1989 (pp. 245–255). San Francisco, CA: Morgan Kaufmann.
   Google Scholar
• Matt, P.A., Toni, F., Stournaras, T., & Dimitrelos, D. (2008). Argumentation-based agents for eProcurement. In M. Berger, B. Burg, & S. Nishiyama (Eds.), Proceedings of the 7th int. conf. on autonomous agents and multiagent systems (AAMAS 2008) – industry and applications track (pp. 71–74), New York, NY: ACM.
   Google Scholar
• Matt, P.A., Toni, F., & Vaccari, J. (2010). Dominant decisions by argumentation agents. In P. McBurney, I. Rahwan, S. Parsons, & N. Maudet (Eds.), Proceedings of the sixth international workshop on argumentation in multi-agent systems (ArgMAS 2009), affiliated to AAMAS 2009, Vol. 6057 of Lecture notes in computer science (pp. 42–59). Berlin, Germany: Springer.
   Google Scholar
• McCarthy, J. (1980). Circumscription – a form of non-monotonic reasoning. Artificial Intelligence, 13, 27–39. doi: 10.1016/0004-3702(80)90011-9
   Web of Science ®Google Scholar
• Modgil, S., & Prakken, H. (2013). A general account of argumentation with preferences. Artificial Intelligence, 195, 361–397. doi: 10.1016/j.artint.2012.10.008
   Web of Science ®Google Scholar
• Pollock, J.L. (1987). Defeasible reasoning. Cognitive Science, 11, 481–518. doi: 10.1207/s15516709cog1104_4
   Web of Science ®Google Scholar
• Prakken, H., & Vreeswijk, G. (2002). Logics for defeasible argumentation. In D. Gabbay & F. Guenthner (Eds.), Handbook of philosophical logic, second edition (pp. 219–318). Dordrecht, he Netherlands: Kluwer Academic Publishers.
   Google Scholar
• Reiter, R. (1980). A logic for default reasoning. Artificial Intelligence, 13, 81–132. doi: 10.1016/0004-3702(80)90014-4
   Web of Science ®Google Scholar
• Sartor, G. (1994). A formal model of legal argumentation. Ratio Juris, 7, 212–226. doi: 10.1111/j.1467-9337.1994.tb00175.x
   Google Scholar
• Schulz, C., & Toni, F. (2013). ABA-based answer set justification (technical communication). Theory and Practice of Logic Programming, on-line supplement, Vol. 13, no. 4–5.
   Google Scholar
• Thang, P., & Luong, H. (2013). Translating preferred subtheories into structured argumentation. Journal of Logic and Computation, to appear.
   Google Scholar
• Toni, F. (2008). Assumption-based argumentation for closed and consistent defeasible reasoning. In K. Satoh, A. Inokuchi, K. Nagao, & T. Kawamura (Eds.), New frontiers in artificial intelligence: JSAI 2007 conference and workshops revised selected papers. Lecture Notes in Computer Science 4914 (pp. 390–402). Berlin, Germany: Springer.
   Google Scholar
• Toni, F. (2012). Reasoning on the web with assumption-based argumentation. In T. Eiter and T. Krennwallner (Eds.), Reasoning web. Semantic technologies for advanced query answering 8th international summer school 2012, Vienna, Austria, September 3-8, 2012. Proceedings. Lecture Notes in Computer Science 7487 (pp. 370–386). Berlin, Germany: Springer.
   Google Scholar
• Toni, F. (2013). A generalised framework for dispute derivations in assumption-based argumentation. Artificial Intelligence, 195, 1–43. doi: 10.1016/j.artint.2012.09.010
   Web of Science ®Google Scholar