In this paper, starting from a generalized coherent (i.e. avoiding uniform loss) interval-valued probability assessment on a finite family of conditional events, we construct conditional probabilities with quasi additive classes of conditioning events which are consistent with the given initial assessment. Quasi additivity assures coherence for the obtained conditional probabilities. In order to reach our goal we define a finite sequence of conditional probabilities by exploiting some theoretical results on g-coherence. In particular, we use solutions of a finite sequence of linear systems.
Sanfilippo, G. (2012). From imprecise probability assessments to conditional probabilities with quasi additive classes of conditioning events. In Uncertainty in artificial intelligence: proceedings of the twenty-eight conference (pp.736-745). Corvallis, Oregon : Association for Uncertainty in Artificial Intelligence.
From imprecise probability assessments to conditional probabilities with quasi additive classes of conditioning events
SANFILIPPO, Giuseppe
2012-01-01
Abstract
In this paper, starting from a generalized coherent (i.e. avoiding uniform loss) interval-valued probability assessment on a finite family of conditional events, we construct conditional probabilities with quasi additive classes of conditioning events which are consistent with the given initial assessment. Quasi additivity assures coherence for the obtained conditional probabilities. In order to reach our goal we define a finite sequence of conditional probabilities by exploiting some theoretical results on g-coherence. In particular, we use solutions of a finite sequence of linear systems.File | Dimensione | Formato | |
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