N. Rosen, A. Einstein, and B. Podolsky, Can Quantum-Mechanical Description of Physical Reality Be Considered Complete ? Physical Review, pp.777-780, 1935.

F. Aguirre, Reliability analysis of systems using belief functions theory to represent epistemic uncertainty, 2012.

A. Aspect, Proposed experiment to test separable hidden-variable theories, Physics Letters A, vol.54, issue.2, pp.117-118, 1935.
DOI : 10.1016/0375-9601(75)90831-2

T. Aven, On the Need for Restricting the Probabilistic Analysis in Risk Assessments to Variability, Risk Analysis, vol.14, issue.3, pp.354-60, 2010.
DOI : 10.1111/j.1539-6924.2009.01314.x

T. Aven, Some reflections on uncertainty analysis and management. Reliability Engineering & System Safety, pp.195-201, 2010.

J. S. Bell, On the Einstein Podolsky Rosen paradox, Physics, vol.1, issue.3, pp.195-200, 1964.

I. Bloch, Incertitude, imprécision et additivité en fusion de données : point de vue historique, Traitement du Signal, vol.13, issue.4, pp.267-288, 1996.

D. Blockley, Analysing uncertainties: Towards comparing Bayesian and interval probabilities', Mechanical Systems and Signal Processing, pp.1-13, 2012.
DOI : 10.1016/j.ymssp.2012.05.007

S. Bradley, Dutch Book Arguments and Imprecise Probabilities of The Philosophy of Science in a European Perspective, Probabilities, Laws, and Structures, pp.3-17

C. Camerer and M. Weber, Recent developments in modeling preferences: Uncertainty and ambiguity, Journal of Risk and Uncertainty, vol.8, issue.4, pp.325-370, 1992.
DOI : 10.1007/BF00122575

R. M. Cooke, The anatomy of the squizzel, Reliability Engineering & System Safety, vol.85, issue.1-3, pp.313-319, 2004.
DOI : 10.1016/j.ress.2004.03.019

D. Dubois, Representation, Propagation, and Decision Issues in Risk Analysis Under Incomplete Probabilistic Information, Risk Analysis, vol.8, issue.1, pp.361-369, 2010.
DOI : 10.1111/j.1539-6924.2010.01359.x

D. Dubois and H. Prade, Representation and combination of uncertainty with belief functions and possibility measures, Computational Intelligence, vol.5, issue.1, pp.244-264, 1988.
DOI : 10.1016/0165-0114(78)90029-5

D. Dubois and H. Prade, Formal Representations of Uncertainty, Decision-making Process : Concepts and Methods, pp.85-156, 2010.
DOI : 10.1002/9780470611876.ch3

P. Simon and L. , Essai philosophique sur les probabilités

E. N. Lorenz, Un battement d'aile de papillon au brésil peut-il déclencher une tornade au texas ? Alliage, pp.42-45, 1993.

D. Warner and N. , Probability theory and consistent reasoning Risk analysis : an official publication of the Society for Risk Analysis, pp.377-80, 2010.

M. and E. Paté-cornell, Uncertainties in risk analysis: Six levels of treatment, Reliability Engineering & System Safety, vol.54, issue.2-3, pp.95-111, 1996.
DOI : 10.1016/S0951-8320(96)00067-1

M. Sallak, W. Schön, and F. Aguirre, Transferable belief model for reliability analysis of systems with data uncertainties and failure dependencies, Proceedings of the Institution of Mechanical Engineers, pp.266-278, 2010.
DOI : 10.1243/1748006XJRR292

URL : https://hal.archives-ouvertes.fr/hal-00522460

M. Sallak, W. Schön, and F. Aguirre, Reliability assessment for multi-state systems under uncertainties based on the Dempster???Shafer theory, IIE Transactions, vol.44, issue.9, p.2012
DOI : 10.1016/S0377-2217(99)00228-3

URL : https://hal.archives-ouvertes.fr/hal-00749606

M. Sallak, C. Simon, and J. Aubry, A Fuzzy Probabilistic Approach for Determining Safety Integrity Level, IEEE Transactions on Fuzzy Systems, vol.16, issue.1, pp.239-248, 2008.
DOI : 10.1109/TFUZZ.2007.903328

URL : https://hal.archives-ouvertes.fr/hal-00167486

W. Schön and T. Denoeux, Prise en compte des incertitudes dans les évaluations de risque à l'aide de fonctions de croyance, 14ème Congrès de Maîtrise des Risques et de Sûreté de Fonctionnement, 2004.

G. Shafer, Non-Additive Probabilities in the Work of Bernoulli and Lambert, Classic Works of the Dempster-Shafer Theory of Belief Functions of Studies in Fuzziness and Soft Computing, pp.117-182, 2008.

D. Nozer and . Singpurwalla, Reliability and Risk : A Bayesian Perspective Wiley series in probability and statistics, 2006.

V. Lev, I. Utkin, and . Kozine, On new cautious structural reliability models in the framework of imprecise probabilities. Structural Safety, pp.411-416, 2010.

P. Vicig and T. Seidenfeld, Bruno de Finetti and imprecision: Imprecise probability does not exist!, International Journal of Approximate Reasoning, vol.53, issue.8, 2012.
DOI : 10.1016/j.ijar.2012.06.021

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.224.740

P. Walley, Statistical reasoning with imprecise probabilities, 1991.
DOI : 10.1007/978-1-4899-3472-7

L. Zadeh, Fuzzy sets, Information and Control, vol.8, issue.3, pp.338-353, 1965.
DOI : 10.1016/S0019-9958(65)90241-X

E. Zio, Reliability engineering : Old problems and new challenges. Reliability Engineering & System Safety, pp.125-141, 2009.
DOI : 10.1016/j.ress.2008.06.002

URL : https://hal.archives-ouvertes.fr/hal-00610053