Handling threats, rewards, and explanatory arguments in a unified setting
2005; Wiley; Volume: 20; Issue: 12 Linguagem: Inglês
10.1002/int.20109
ISSN1098-111X
Autores Tópico(s)Access Control and Trust
ResumoInternational Journal of Intelligent SystemsVolume 20, Issue 12 p. 1195-1218 Research Article Handling threats, rewards, and explanatory arguments in a unified setting Leila Amgoud, Corresponding Author Leila Amgoud [email protected] Institut de Recherche en Informatique de Toulouse (IRIT), 118, Route de Narbonne, 31062 Toulouse, FranceInstitut de Recherche en Informatique de Toulouse (IRIT), 118, Route de Narbonne, 31062 Toulouse, FranceSearch for more papers by this authorHenri Prade, Henri Prade [email protected] Institut de Recherche en Informatique de Toulouse (IRIT), 118, Route de Narbonne, 31062 Toulouse, FranceSearch for more papers by this author Leila Amgoud, Corresponding Author Leila Amgoud [email protected] Institut de Recherche en Informatique de Toulouse (IRIT), 118, Route de Narbonne, 31062 Toulouse, FranceInstitut de Recherche en Informatique de Toulouse (IRIT), 118, Route de Narbonne, 31062 Toulouse, FranceSearch for more papers by this authorHenri Prade, Henri Prade [email protected] Institut de Recherche en Informatique de Toulouse (IRIT), 118, Route de Narbonne, 31062 Toulouse, FranceSearch for more papers by this author First published: 14 October 2005 https://doi.org/10.1002/int.20109Citations: 17AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Abstract Current logic-based handling of arguments has mainly focused on explanation or justification-oriented purposes in presence of inconsistency. So only one type of argument has been considered, and several argumentation frameworks have then been proposed for generating and evaluating such arguments. However, recent works on argumentation-based negotiation have emphasized different other types of arguments such as threats, rewards, and appeals. The purpose of this article is to provide a logical setting that encompasses the classical argumentation-based framework and handles the new types of arguments. More precisely, we give the logical definitions of these arguments and their weighting systems. These definitions take into account that negotiation dialogues involve not only agents' beliefs (of various strengths), but also their goals (having maybe different priorities), as well as the beliefs on the goals of other agents. In other words, from the different beliefs and goals bases maintained by agents, all the possible threats, rewards, explanations, and appeals that are associated with them can be generated. It may also happen that an intended threat, or reward, is not perceived as such by the addressee and thus misses its target because the addresser misrepresents the addressee's goals. The proposed approach accounts for that phenomenon. Finally, we show how to evaluate conflicting arguments of different types. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 1195–1218, 2005. References 1 Cohen PR. Heuristic reasoning about uncertainty: An artificial intelligence approach. Marshfield, MA: Pitman Publishing, Inc.; 1984. 2 Krause P, Ambler S, Elvang-Gøransson M, Fox J. A logic of argumentation for reasoning under uncertainty. Comput Intell 1995; 11: 113– 131. 3 Pollock JL. Defeasible reasoning with variable degrees of justification. J Artif Intell 2001; 333: 233– 282. 4 Amgoud L, Cayrol C. Inferring from inconsistency in preference-based argumentation frameworks. Int J Autom Reason 2002; 29: 125– 169. 5 Amgoud L, Cayrol C. A reasoning model based on the production of acceptable arguments. Ann Math Artif Intell 2002; 34: 197– 216. 6 Dung, PM. On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artif Intell 1995; 77: 321– 357. 7 Pollock JL. How to reason defeasibly. J Artif Intell 1992; 57: 1– 42. 8 Prakken H, Sartor G. Argument-based extended logic programming with defeasible priorties. J Appl Non-Classical Logics 1997; 7: 25– 75. 9 Simari GR, Loui RP. A mathematical treatment of defeasible reasoning and its implementation. J Artif Intell 1992; 53: 125– 157. 10 Amgoud L, Maudet N, Parsons S. Modelling dialogues using argumentation. In: Kraus S, Nakashima H, Tambe M, editors. Proc 4th Int Conf on Multi-Agent Systems, Boston, MA. Los Alamitos, CA: IEEE Computer Society Press; 2000. pp 31– 38. 11 Amgoud L, Parsons S, Maudet N. Arguments, dialogue, and negotiation. In: Proc 14th European Conf on Artificial Intelligence. Amsterdam: IOS Press; 2000. pp 338– 342. 12 Amgoud L, Prade H. Reaching agreement through argumentation: A possibilistic approach. In: Dubois D, Welty C, Williams MA, editors. Proc 9th Int Conf on the Principles of Knowledge Representation and Reasoning, Whistler, Canada. Menlo Park, CA: AAAI Press; 2004. pp 175– 182. 13 Kraus S, Sycara K, Evenchik A. Reaching agreements through argumentation: A logical model and implementation. J Artif Intell 1998; 104: 1– 69. 14 Parsons S, Sierra C, Jennings NR. Agents that reason and negotiate by arguing. J Logic Comput 1998; 8(3): 261– 292. 15 Rahwan I, Ramchurn SD, Jennings NR, McBurney P, Parsons S, Sonenberg L. Argumentation-based negotiation. Knowl Eng Rev 2004; 18(4): 343– 375. 16 Rahwan I, Sonenberg L, Dignum F. Towards interest-based negotiation. In: Proc 2nd Int Conf on Autonomous Agents and Multi-Agent Systems, Melbourne, Australia, July 2003. New York: ACM Press; 2003. pp 773– 780. 17 Ramchurn SD, Jennings N, Sierra C. Persuasive negotiation for autonomous agents: A rhetorical approach. In: Proc IJCAI Workshop on Computational Models of Natural Arguments; 2003. 18 Berrached A, Beheshti M, de Korvin A, Al R. Applying fuzzy relation equations to threat analysis. In: Proc 35th Annual Hawaii Int Conf on System Sciences, vol. 2; 2002. pp 50– 54. 19 Hamed E, Graham J, Elmaghraby A. Computer system threat evaluation. In: Proc 10th Int Conf on Intelligent Systems, Washington, D.C. Raleigh, NC: International Society for Computers and Their Applications; 2001. pp 23– 26. 20 Hamed E, Graham J, Elmaghraby A. Fuzzy threat evaluation in computer security. In: Proc Int Conf on Computers and Their Applications, San Francisco, CA. Raleigh, NC: International Society for Computers and Their Applications; 2002. pp 389– 393. 21 Amgoud L, Prade H. Formal handling of threats and rewards in a negotiation dialogue. In: Proc 4th Int Joint Conf on Autonomous Agents and Multi-Agent Systems. New York: ACM Press; 2005. pp 529– 536. 22 Toulmin S, Reike R, Janik A. An introduction to reasoning. New York: Macmillan Publishing Company, Inc.; 1979. 23 Karlins M, Abelson HI. Persuasion: How opinions and attitudes are changed. Spinger Publishing Company, Inc.; 1970. 24 O'Keefe DJ. Persuasion: Theory and research. SAGE Publications; 1990. 25 Pruitt, DG. Negotiation behavior. New York: Academic Press; 1981. 26 Amgoud L, Cayrol C, LeBerre D. Comparing arguments using preference orderings for argument-based reasoning. In: Proc 8th Int Conf on Tools with Artificial Intelligence; 1996. pp 400– 403. 27 Fargier H, Lang J, Schiex T. Selecting preferred solutions in fuzzy constraint satisfaction problems. In: Proc 1st European Congress on Fuzzy and Intelligent Technologies, EUFIT'93; 1993. pp 1128– 1134. 28 Moulin H. Axioms of cooperative decision making. Cambridge, UK: Cambridge University Press; 1988. 29 Dubois D, Le Berre D, Prade H, Sabbadin R. Logical representation and computation of optimal decisions in a qualitative setting. In: 15th National Conf on Artificial Intelligence (AAAI-98). Menlo Park, CA: AAAI Press; 1998. pp 588– 593. 30 Dubois D, Prade H, Sabbadin, R. Decision-theoretic foundations of qualitative possibility theory. Eur J Op Res 2001; 128: 459– 478. 31 Dubois D, Lang J, Prade H. Possibilistic logic. In: DM Gabbay, editor. Handbook of logic in artificial intelligence and logic programming, vol. 3. Oxford, UK: Clarendon Press; 1994. pp 439– 513. Citing Literature Volume20, Issue12December 2005Pages 1195-1218 ReferencesRelatedInformation
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