European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty

ECSQARU 2015: Symbolic and Quantitative Approaches to Reasoning with Uncertainty pp 541-551 | Cite as

Variable Elimination for Interval-Valued Influence Diagrams

  • Rafael Cabañas
  • Alessandro Antonucci
  • Andrés Cano
  • Manuel Gómez-Olmedo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9161)


Influence diagrams are probabilistic graphical models used to represent and solve decision problems under uncertainty. Sharp numerical values are required to quantify probabilities and utilities. Yet, real models are based on data streams provided by partially reliable sensors or experts. We propose an interval-valued quantification of these parameters to gain realism in the modelling and to analyse the sensitivity of the inferences with respect to perturbations of the sharp values. An extension of the classical influence diagrams formalism to support interval-valued potentials is provided. Moreover, a variable elimination algorithm especially designed for these models is developed and evaluated in terms of complexity and empirical performances.


Influence diagrams Bayesian networks Credal networks Sequential decision making Imprecise probability 



This research was supported by the Spanish Ministry of Economy and Competitiveness under project TIN2013-46638-C3-2-P, the European Regional Development Fund (FEDER), the FPI scholarship program (BES-2011-050604) and the short stay in foreign institutions scholarship EEBB-I-14-08102. The authors have also been partially supported by “Junta de Andalucía” under projects TIC-06016 and P08-TIC-03717.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Rafael Cabañas
    • 1
  • Alessandro Antonucci
    • 2
  • Andrés Cano
    • 1
  • Manuel Gómez-Olmedo
    • 1
  1. 1.Department of Computer Science and Artificial Intelligence CITICUniversity of GranadaGranadaSpain
  2. 2.Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA)Manno-LuganoSwitzerland

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