.. Système-de-décisiondécisionà-base-d-'arguments, 62 4.2.2 Une typologie formelle de l'argument pratique, p.68

E. Ext, Considérons Puisque E / ? Ext(VSAF), en accord avec la Définition 5, il y a deux possibilités : 1. V est irréflexive : Considérons que V est réflexive, val(?)) ? Pref, or ceci n'est pas possiblé etant donné que Pref est irréflexive

V. Est-transitive, Soit ?, ?, ? ? A, considérons que (?, ?)? V , (?, ?) ? V et (?

?. Pref, Cependant, puisque Pref est transitive, ` a partir de (1) et (2) il s'ensuit que V est transitive

E. Ext, ?. Ext, E. Vaf-)-et, E. Puisque, and . Ext, Considérons, PAF V ) et en accord avec la Définition 5, E n'est pas une extension admissible pour PAF V , i.e il y a deux possibilités

. Pref, En accord avec la Définition 21, il s'ensuit que (?, ?) ? defeats. E n'est donc pas sans-conflit pour VAF

V. Def and ?. Tel-que, Def V (Def V est construitàconstruit`construità partir de R et V en accord avec la Définition 19 et la Définition 29) Puisque (?, ?) ? Def V , on a (?, ?) ? R et (?, ?) / ? V , i.e par la Définition 29, (?, ?) ? R et (val(?), val(?)) / ? Pref, i.e en accord avec la Définition 21, (?, ?) ? defeats. Puisque E est une extension admissible pour VAF, il se verifie que ? ? ? E tel que (?, ?) ? defeats, i.e (?, ?) ? R et, Pref, i.e (?, ?) ? R et (?, ?) / ? V , i.e (?, ?) ? Def V . Ceci contredit le fait que E ne défende pas tous sesélémentsseséléments dans PAF V

E. Ext, Soit E une extension admissible pour PAF V . Considérons que E / ? Ext(VAF) Ce qui signifie que E n'est pas une extension admissible pour VAF. En accord [AB09] L. Amgoud and P. Besnard. Bridging the gap between abstract argumentation systems and logic, Scalable Uncertainty Management, pp.12-27, 2009.

L. Amgoud and P. Besnard, A Formal Analysis of Logic-Based Argumentation Systems, Scalable Uncertainty Management, pp.42-55, 2010.
DOI : 10.1007/978-3-642-15951-0_10

C. [. Amgoud and . Cayrol, A reasoning model based on the production of acceptable arguments, Annals of Mathematics and Artificial Intelligence, vol.34, issue.1/3, pp.197-216, 2002.
DOI : 10.1023/A:1014490210693

C. [. Amgoud, D. L. Cayrol, and . Berre, Comparing arguments using preference orderings for argument-based reasoning, Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence, pp.400-403, 1996.
DOI : 10.1109/TAI.1996.560731

]. L. Amg99 and . Amgoud, ContributionàContributionà l'intégration des préférences dans le raisonnement argumentatif, Thèse de doctorat, 1999.

H. [. Amgoud and . Prade, Using arguments for making and explaining decisions, Artificial Intelligence, vol.173, issue.3-4, pp.413-436, 2009.
DOI : 10.1016/j.artint.2008.11.006

S. [. Amgoud, L. Parsons, and . Perrussel, An argumentation framework based on contextual preferences, Proceedings of the International Conference on Formal and Applied and Practical Reasoning, pp.59-67, 2000.

]. K. Ash91 and . Ashley, Modeling Legal Arguments : Reasoning with Cases and Hypotheticals, 1991.

]. L. Av09a, S. Amgoud, and . Vesic, On revising argumentation-based decision systems, European Conference of Symbolic and Quantitative Approaches to Reasoning with Uncertainty, pp.71-82, 2009.

]. L. Av09b, S. Amgoud, and . Vesic, Repairing preference-based argumentation frameworks, International Joint Conference on Artificial Intelligence, pp.665-670, 2009.

[. Bourguet, L. Amgoud, and R. Thomopoulos, Contribution aux comparaisons formelles des modèles de préférences en argumentation, Journées Francophones des Modèles formels de l'intéraction, pp.81-92, 2009.

[. Bourguet, L. Amgoud, and R. Thomopoulos, Towards a Unified Model of Preference-Based Argumentation, International Symposium of Foundations of Information and Knowledge Systems, pp.326-344, 2010.
DOI : 10.1007/978-3-642-11829-6_21
URL : https://hal.archives-ouvertes.fr/lirmm-00538789

. M. Bbl-+-08-]-j-., A. Bourre, M. Bégat, V. Leroux, N. Mousques-cami et al., Valeur nutritionnelle (macro et micro-nutriments) de farines et pains français, Médecine et Nutrition, vol.44, issue.2, pp.49-76, 2008.

. [. Bench-capon, Persuasion in Practical Argument Using Value-based Argumentation Frameworks, Journal of Logic and Computation, vol.13, issue.3, pp.429-448, 2003.
DOI : 10.1093/logcom/13.3.429

P. [. Bench-capon and . Dunne, Argumentation in artificial intelligence, Artificial Intelligence, vol.171, issue.10-15, pp.10-15619, 2007.
DOI : 10.1016/j.artint.2007.05.001

J. Baget, M. Croitoru, J. Fortin, and R. Thomopoulos, Default Conceptual Graph Rules: Preliminary Results for an Agronomy Application, ICCS, pp.86-99, 2009.
DOI : 10.1007/978-3-540-73681-3_7
URL : https://hal.archives-ouvertes.fr/lirmm-00410640

J. Bourguet, B. Cuq, A. Ndiaye, and R. Thomopoulos, Modelling a dynamic process in the conceptual graph model : Extension needed, International Conference on Conceptual Structures (Supplement), pp.49-56, 2008.
URL : https://hal.archives-ouvertes.fr/hal-01123359

P. [. Bondarenko, R. A. Dung, F. Kowalski, and . Toni, An abstract, argumentation-theoretic approach to default reasoning, Artificial Intelligence, vol.93, issue.1-2, pp.63-101, 1997.
DOI : 10.1016/S0004-3702(97)00015-5

M. [. Birnbaum, R. Flowers, and . Mcguire, Towards an ai model of argumentation, Association for the Advancement of Artificial Intelligence, pp.313-315, 1980.

A. [. Besnard and . Hunter, Elements of Argumentation, 2008.
DOI : 10.7551/mitpress/9780262026437.001.0001

[. Ber, J. Lieber, and A. Napoli, Les systèmessystèmesà base de connaissances, Encyclopédie de l'informatique et des systèmes d'information, pp.1197-1208, 2006.

B. [. Bentahar, M. Moulin, and . Bélanger, A taxonomy of argumentation models used for knowledge representation, Artificial Intelligence Review, vol.9, issue.4, pp.211-259, 2010.
DOI : 10.1007/s10462-010-9154-1

]. D. Bou90 and . Bouyssou, Building criteria : A prerequisite for mcda, Readings in Multiple Criteria Decision Aid, pp.58-80

[. Cadinno, Information, choix, consommateurs responsables : des leviers pour un développement durable ? http://www.melissa.ens-cachan, Car10] Carneades. Argumentation system, 2008.

C. Cayrol, On the relation between argumentation and non-monotonic coherence-based entailment, International Joint Conference on Artificial Intelligence, pp.1443-1448, 1995.

T. [. Chorley and . Bench-capon, An empirical investigation of reasoning with legal cases through theory construction and application, Artificial Intelligence and Law, vol.1, issue.1, pp.323-371, 2005.
DOI : 10.1007/s10506-006-9016-y

C. Cayrol, S. Doutre, M. Lagasquie-schiex, and J. Mengin, Minimal defence : a refinement of the preferred semantics for argumentation frameworks, 9th International Workshop on Non-Monotonic Reasoning, pp.408-415, 2002.
URL : https://hal.archives-ouvertes.fr/hal-00133893

M. [. Chein and . Mugnier, Graph-based Knowledge Representation and Reasoning , Computational Foundations of Conceptual Graphs. Advanced Information and Knowledge Processing Series, 2008.

. Cmdk-+-07-]-s, C. Coste-marquis, S. Devred, M. Konieczny, P. Lagasquie-schiex et al., On the merging of dung's argumentation systems, Artificial Intelligence Journal, vol.171, pp.730-753, 2007.

T. [. Dunne and . Bench-capon, Complexity and combinatorial properties of argument systems, 2001.

[. Dinabio, Proceedings of dinabio développement et innovation en agriculture biologique. http://www.inra.fr/ciag/revue_innovations_agronomiques/ volume_4_janvier_2009, Dimopoulos, P. Moraitis, and L. Amgoud. Characterizing the outcomes of argumentation-based integrative negotiation. In Intelligent Agent Technology, pp.456-460, 2008.

. [. Dubuisson-quellier, De la routinè a la délibération. les arbitrages des consommateurs en situation d'achat. Réseaux, pp.253-284, 2006.

]. M. Dsa-+-07, R. Dean, A. Sheperd, P. Arvola, L. Lampila et al., Report on consumer expectations of health benefits of modified cereal products, 2007.

]. P. Dun95 and . Dung, On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games, Artificial Intelligence Journal, vol.77, pp.321-357, 1995.

M. Elvang-gøransson, P. Krause, and J. Fox, Dialectic reasoning with inconsistent information, In Uncertainty in Artificial Intelligence, pp.114-121, 1993.
DOI : 10.1016/B978-1-4832-1451-1.50018-4

[. Fcn and . Fibres, [Fis70] P. Fishburn. Utility Theory for Decision Making, 1970.

. Glm-+-09-]-e, Y. Ginon, C. Lohérac, P. Martin, S. Combris et al., Effect of fibre information on consumer willingness to pay for french baguettes, Food Quality and Preference, vol.20, pp.343-352, 2009.

]. J. Got98 and . Gottsegen, Using argumentation analysis to assess stakeholder interests in planning debates, Computers, Environment and Urban Systems, vol.22, issue.4, pp.365-379, 1998.

]. T. Gru93 and . Gruber, A translation approach to portable ontology specifications, KNOW- LEDGE ACQUISITION, vol.5, pp.199-220, 1993.

]. N. Gua98 and . Guarino, Formal ontology and information systems, pp.3-15, 1998.

R. [. Kakas, F. Kowalski, and . Toni, Abductive Logic Programming, Journal of Logic and Computation, vol.2, issue.6, pp.719-770, 1992.
DOI : 10.1093/logcom/2.6.719

]. S. Kvdt08, L. Kaci, and . Van-der-torre, Preference-based argumentation : Arguments supporting multiple values, International Journal of Approximate Reasoning, vol.48, issue.3, pp.730-751, 2008.

L. [. Maguire and . Boiney, Resolving Environmental Disputes: a Framework Incorporating Decision Analysis and Dispute Resolution Techniques, Journal of Environmental Management, vol.42, issue.1, pp.31-48, 1994.
DOI : 10.1006/jema.1994.1058

[. Mugnier and M. Chein, Polynomial algorithms for projection and matching, Workshop on Conceptual Graphs, pp.239-251, 1992.
DOI : 10.1007/3-540-57454-9_19

]. J. Mcc79 and . Mccarthy, First order theories of individual concepts and propositions Moulin and H. Irandoust. Extending the conceptual graph approach to represent evaluative attitudes in discourse, Machine Intelligence International Conference on Conceptual Structures, pp.140-153, 1979.

]. V. Mou03 and . Mousseau, Elicitation des préférences pour l'aide multicritèrè a la décision. HabilitationàHabilitationà diriger des recherches, 2003.

J. [. De-moor, M. Park, and . Croitoru, Argumentation map generation with conceptual graphs : the case for essence, CS-TIW at International Conference on Conceptual Structures, pp.58-69, 2009.
URL : https://hal.archives-ouvertes.fr/lirmm-00410627

C. [. Olbrechts-tyteca and . Perelman, Traité de l'argumentation : La nouvelle rhétorique, 1958.

]. C. Pie79 and . Pierce, Collected papers, 1979.

]. J. Pnn10a-]-pnnspol92 and . Pollock, http://www.sante.gouv.fr/htm/pointsur/ nutrition/pol_nutri4.htm, 2010. [PNN10b] PNNS (website) http://www.mangerbouger.fr/menu-secondaire/pnns/ le-pnns How to reason defeasibly, Artificial Intelligence, vol.57, issue.1, pp.1-42, 1992.

]. H. Pra93 and . Prakken, A logical framework for modelling legal argument, International Conference on Artificial Intelligence and Law, pp.1-9, 1993.

]. H. Pra02 and . Prakken, An exercise in formalising teleological case-based reasoning, Artificial Intelligence Law, vol.10, issue.1-3, pp.113-133, 2002.

G. [. Prakken and . Sartor, Argument-based extended logic programming with defeasible priorities, Journal of Applied Non-Classical Logics, vol.53, issue.1993, pp.25-75, 1997.
DOI : 10.1080/11663081.1997.10510900

D. [. Roy and . Bouyssou, Aide Multicritèrè a la Décision : Méthodes et Cas, Economica, 1993.

]. R. Rei80 and . Reiter, A logic for default reasoning, Artificial Intelligence, vol.13, pp.81-132, 1980.

F. [. Rémésy and . Leenhardt, L'amélioration de la valeur nutritionnelle des pains bio. http://www.itab.asso.fr/downloads/evenements/ qualite-nutrition-cplt-remesy.pdf, 2009. [Ros91] E. Rosinger. Beyond preference information based multiple criteria decision making, European Journal of Operational Research, vol.53, pp.217-227, 1991.

]. B. Roy85 and . Roy, Méthodologie multicritère d'aidè a la décision, Economica, 1985.

G. [. Rahwan and . Simari, Argumentation in Artificial Intelligence, 2009.

D. [. Roy and . Vanderpooten, An overview on ???The European school of MCDA: Emergence, basic features and current works???, European Journal of Operational Research, vol.99, issue.1, pp.26-27, 1997.
DOI : 10.1016/S0377-2217(96)00379-7

]. G. Sar93 and . Sartor, Defeasible arguments in a logic programming model, Gruppo ricercatori e Utenti di Logic Programming (GULP), pp.423-440, 1993.

L. J. Savage, The foundation of statistics, 1954.

D. [. Dubois and H. Prade, Argumentative inference in uncertain and inconsistent knowledge bases, In Uncertainty in Artificial Intelligence, pp.411-419, 1993.

H. [. Slavin and . Green, Dietary fibre and satiety, Nutrition Bulletin, vol.58, issue.s1, pp.32-42, 2007.
DOI : 10.1079/BJN19800003

A. [. Stolzenburg, C. I. García, G. R. Chesñevar, and . Simari, Computing Generalized Specificity, Journal of Applied Non-Classical Logics, vol.90, issue.4, pp.87-113, 2003.
DOI : 10.3166/jancl.13.87-113
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.1444

]. H. Sim55 and . Simon, A behavourial model of rational choice, Quaterly Journal of Economics, vol.69, pp.99-118, 1955.

R. [. Simari and . Loui, A mathematical treatment of defeasible reasoning and its implementation, Artificial Intelligence, vol.53, issue.2-3, pp.125-157, 1992.
DOI : 10.1016/0004-3702(92)90069-A

E. Salvat and M. Mugnier, Sound and complete forward and backward chainingd of graph rules, ICCS, pp.248-262, 1996.

]. J. Sow84 and . Sowa, Conceptual Structures : Information Processing in Mind and Machine, 1984.

]. A. Tar56 and . Tarski, On Some Fundamental Concepts of Metamathematics, 1956.

[. Thomopoulos, J. Bourguet, B. Cuq, and A. Ndiaye, Answering queries that may have results in the future : A case study in food science. Knowledge-Based Systems, pp.491-495, 2010.

G. [. Tohmé, G. R. Bodanza, and . Simari, Aggregation of Attack Relations: A Social-Choice Theoretical Analysis of Defeasibility Criteria, Foundations of Information and Knowledge Systems, pp.8-23, 2008.
DOI : 10.1007/978-3-540-77684-0_4

]. S. Tou69 and . Toulmin, The Uses of Argument, 1969.

H. [. Vreeswijk and . Prakken, Credulous and Sceptical Argument Games for Preferred Semantics, Proceedings of the 7th European Workshop on Logic for Artificial Intelligence, number 1919 in Springer Lecture Notes in AI, pp.239-253, 2000.
DOI : 10.1007/3-540-40006-0_17

]. R. Yag08 and . Yager, Entropy and specificity in a mathematical theory of evidence, Classic Works of the Dempster-Shafer Theory of Belief Functions, pp.291-310, 2008.