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).
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(Document in English)
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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) |
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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) |
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Deposited On: | 25 May 2020 14:38 |
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