Imprecise probability in graphical models: achievements and challenges

Authors:
Serafín Moral
Affiliations:
Departamento de Ciencias de la Computación e I.A., Universidad de Granada, Granada, Spain
Venue:
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Year:
2005

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Abstract

This talk will review the basic notions of imprecise probability following Walley's theory [1] and its application to graphical models which usually have considered precise Bayesian probabilities [2]. First approaches to imprecision were robustness studies: analysis of the sensibility of the outputs to variations of network parameters [3,4]. However, we will show that the role of imprecise probability in graphical models can be more important, providing alternative methodologies for learning and inference.