Abstract
This short overview paper provides a preliminary investigation of the potentials of possibilistic logic in decision analysis. Indeed a possibilistic logic base can not only be seen as a set of more or less certain pieces of information (which was the original understanding when possibilistic logic was introduced), but also as a layered set of propositions expressing goal shaving different levels of priority. The paper surveys applications to multiple criteria decision (specification of preferences and goals, modeling of various types of aggregation and weighting procedures), and to decision under uncertainty. Preference revision or combination, and analysis of conflicts between goals are also briefly discussed. The possibilistic logic framework clearly supports a qualitative view of decision based on the use of ordinal scales.
This paper is a slightly expanded and revised version of two papers with the same title which appear in the unpublished proceedings of the 3rdEurop. Workshop on Fuzzy Decision Analysis and Neural Networks for Management, Planning and Optimization (EFDAN’98, Dortmund, June 16–17, 1998, R. Felix, ed., pp. 40–49), and respectively in the ones of the European Conference in Artificial Intelligence Workshop n°ll“Decision Theory meets Artificial Intelligence: Qualitative and Quantitative Approaches” (Brighton, Aug. 25,1998, J. Lang, ed.,pp. 11–21).
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Dubois, D., Prade, H. (1999). Possibilistic Logic in Decision. In: Chen, G., Ying, M., Cai, KY. (eds) Fuzzy Logic and Soft Computing. The International Series on Asian Studies in Computer and Information Science, vol 6. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5261-1_1
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DOI: https://doi.org/10.1007/978-1-4615-5261-1_1
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