OATAO - Open Archive Toulouse Archive Ouverte Open Access Week

Algorithms for Multi-criteria optimization in Possibilistic Decision Trees

Ben Amor, Nahla and Essghaier, Fatma and Fargier, Hélène Algorithms for Multi-criteria optimization in Possibilistic Decision Trees. (2017) In: Symbolic and Quantitative Approaches to Reasoning with Uncertainty - 14th European Conference, ECSQARU 2017, 10 July 2017 - 14 July 2017 (Lugano, Switzerland).

[img]
Preview
(Document in English)

PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
402kB

Official URL: https://doi.org/10.1007/978-3-319-61581-3_27

Abstract

This paper raises the question of solving multi-criteria sequential decision problems under uncertainty. It proposes to extend to possibilistic decision trees the decision rules presented in [1] for non sequential problems. It present a series of algorithms for this new framework: Dynamic Programming can be used and provide an optimal strategy for rules that satisfy the property of monotonicity. There is no guarantee of optimality for those that do not - hence the definition of dedicated algorithms. This paper concludes by an empirical comparison of the algorithms.

Item Type:Conference or Workshop Item (Paper)
HAL Id:hal-02639577
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Institut Supérieur de Gestion de Tunis (TUNISIA)
Other partners > Université de Tunis (TUNISIA)
Laboratory name:
Statistics:download
Deposited On:25 May 2020 14:38

Repository Staff Only: item control page