TY - GEN
T1 - Irrelevance and independence axioms in Quasi-Bayesian theory
AU - Cozman, Fabio Gagliardi
PY - 1999/1/1
Y1 - 1999/1/1
N2 - © Springer-Verlag Berlin Heidelberg 1999. This paper investigates Walley’s concepts of irrelevance and independence, as applied to the theory of closed convex sets of probability measures. Walley’s concepts are analyzed from the perspective of axioms for conditional independence (the so-called semi-graphoid axioms). Two new results are demonstrated in discrete models: rst, Walley’s concept of irrelevance is an asymmetric semi-graphoid; second, Walley’s concept of independence is an incomplete semi-graphoid. These results are the basis for an understanding of irrelevance and independence in connection to the theory of closed convex sets of probability measures, a theory that has received attention as a powerful representation for uncertainty in beliefs and preferences.
AB - © Springer-Verlag Berlin Heidelberg 1999. This paper investigates Walley’s concepts of irrelevance and independence, as applied to the theory of closed convex sets of probability measures. Walley’s concepts are analyzed from the perspective of axioms for conditional independence (the so-called semi-graphoid axioms). Two new results are demonstrated in discrete models: rst, Walley’s concept of irrelevance is an asymmetric semi-graphoid; second, Walley’s concept of independence is an incomplete semi-graphoid. These results are the basis for an understanding of irrelevance and independence in connection to the theory of closed convex sets of probability measures, a theory that has received attention as a powerful representation for uncertainty in beliefs and preferences.
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M3 - Conference contribution
SN - 354066131X
SN - 9783540661313
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 128
EP - 136
BT - Irrelevance and independence axioms in Quasi-Bayesian theory
T2 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Y2 - 1 January 2018
ER -