Abstract
In this lecture, I expound and comment on a model, or even more ambitiously, a theory, for representing, and drawing inferences from, vague probability assessments. The details of this theory have been published in two papers, the first [3] dealing with its behavioural underpinnings, and the second [1, 2] with its deeper mathematical aspects.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
G. de Cooman. A behavioural model for vague probability assessments. Fuzzy Sets and Systems, 154:305–358, 2005. With discussion.
G. de Cooman. Further thoughts on possibilistic previsions: a rejoinder. Fuzzy Sets and Systems, 154:375–385, 2005.
G. de Cooman and P. Walley. A possibilistic hierarchical model for behaviour under uncertainty. Theory and Decision, 52:327–374, 2002.
P. Walley. Statistical Reasoning with Imprecise Probabilities. Chapman and Hall, London, 1991.
L. A. Zadeh. Fuzzy probabilities. Information Processing and Management, 20:363–372, 1984.
L. A. Zadeh. Toward a perception-based theory of probabilistic reasoning with imprecise probabilities. Journal of Statistical Planning and Inference, 105:233–264, 2002.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer
About this chapter
Cite this chapter
Cooman, G.d. (2006). Reasoning with Vague Probability Assessments. In: Lawry, J., et al. Soft Methods for Integrated Uncertainty Modelling. Advances in Soft Computing, vol 37. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-34777-1_2
Download citation
DOI: https://doi.org/10.1007/3-540-34777-1_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34776-7
Online ISBN: 978-3-540-34777-4
eBook Packages: EngineeringEngineering (R0)