Explaining qualitative decision under uncertainty by argumentation

Proceedings of the National Conference on Artificial Intelligence

Volumn 1, Issue , 2006, Pages 219-224

  Amgoud, Leila ^a   Prade, Henri ^a  

^a CNRS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; PROBLEM SOLVING; UNCERTAIN SYSTEMS;

ATTACKING ARGUMENTS; DECISION PROCESS; PESSIMISTIC DECISION;

DECISION THEORY;

EID: 33750721312     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. Amgoud, L., and Cayrol, C. 2002. Inferring from inconsistency in preference-based argumentation frameworks. In ternational Journal of Automated Reasoning Volume 29, N2:125-169.
2. Amgoud, L., and Prade, H. 2004. Using arguments for making decisions. In Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence, 10-17.
3. Benferhat, S.; Dubois, D.; and Prade, H. 1992. Representing default rules in possibilistic logic. In Proceedings of the 3rd International Conference on Knowledge Representation and Reasoning, 673-684.
4. Bonet, B., and Geffner, H. 1996. Arguing for decisions: A qualitative model of decision making. In Proceedings of the 12th Conference on Uncertainty in Artificial Intelligence, 98-105.
5. Dubois, D.; Berre, D. L.; Prade, H.; and Sabbadin, R. 1999a. Using possibilistic logic for modeling qualitative decision: Alms-based algorithms. Fundamenta Informaticae 37:1-30.
6. Dubois, D.; Godo, L.; Prade, H.; and Zapico, A. 1999b. On the possibilistic decision model: from decision under uncertainty to case-based decision. Int. J. of Uncert., Fuzziness and Knowledge-Based Syst. 7:6:631-670.
7. Dubois, D.; Grabisch, M.; Modave, F.; and Prade, H. 2000. Relating decision under uncertainty and multicriteria decision making models. International Journal of Intelligent Systems 15:967-979.
8. Dubois, D.; Lang, J.; and Prade, H. 1994. Automated reasoning using possibilistic logic: semantics, belief revision and variable certainty weights. IEEE Trans. on Data and Knowledge Engineering 6:64-71.
9. Dubois, D.; Prade, H.; and Sabbadin, R. 2001. Decision-theoretic foundations of qualitative possibility theory. European Journal of Operational Research 128:459-478.
10. Fargier, H., and Sabbadin, R. 2003. Qualitative decision under uncertainty: back to expected utility. In Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI'03.
11. Fox, J., and Parsons, S. 1997. On using arguments for reasoning about actions and values. In Proceedings of the AAAI Spring Symposium on Qualitative Preferences in Deliberation and Practical Reasoning, Stanford.
12. Giang, P. H., and Shenoy, P. 2004. Two axiomatic approaches to decision making using possibility theory. European Journal of Operational Research 162:2:450-467.
13. Kraus, S.; Lehmann, D.; and Magidor, M. 1990. Nonmonotonic reasoning, preferential models and cumulative logics. Artificial Intelligence 44:167-207.
14. Prakken, H., and Sartor, G. 1997. Argument-based extended logic programming with defeasible priorties. Journal of Applied Non-Classical Logics 7:25-75.
15. Simari, G. R., and Loui, R. P. 1992. A mathematical treatment of defeasible reasoning and its implementation. Artificial Intelligence and Law 53:125-157.
16. Tan, S. W., and Pearl, J. 1994. Qualitative decision theory. In Proceedings of the 11th National Conference on Artificial Intelligence, 928-933.