Independence concepts for convex sets of probabilities

Authors:
Luis M. De Campos;Serafin Moral
Affiliations:
Departamento de Ciencias de la Computación e I.A., Universidad de Granada, Granada, Spain;Departamento de Ciencias de la Computación e I.A., Universidad de Granada, Granada, Spain
Venue:
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Year:
1995

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Abstract

In this paper we study different concepts of independence for convex sets of probabilities. There will be two basic ideas for independence. The first is irrelevance. Two variables are independent when a change on the knowledge about one variable does not affect the other. The second one is factorization. Two variables are independent when the joint convex set of probabilities can be decomposed on the product of marginal convex sets. In the case of the Theory of Probability, these two starting points give rise to the same definition. In the case of convex sets of probabilities, the resulting concepts will be strongly related, but they will not be equivalent. As application of the concept of independence, we shall consider the problem of building a global convex set from marginal convex sets of probabilities.