Algorithms for Multi-criteria Optimization in Possibilistic Decision Trees

  • Nahla Ben Amor
  • Fatma Essghaier
  • Hélène Fargier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10369)

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.

Keywords

Possibility theory Sequential decision problems Multi-criteria decision making Decision trees 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Nahla Ben Amor
    • 1
  • Fatma Essghaier
    • 1
    • 2
  • Hélène Fargier
    • 2
  1. 1.LARODECLe BardoTunisia
  2. 2.IRITToulouseFrance

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