12,019 research outputs found
Scientific Polarization
Contemporary societies are often "polarized", in the sense that sub-groups
within these societies hold stably opposing beliefs, even when there is a fact
of the matter. Extant models of polarization do not capture the idea that some
beliefs are true and others false. Here we present a model, based on the
network epistemology framework of Bala and Goyal ["Learning from neighbors",
\textit{Rev. Econ. Stud.} \textbf{65}(3), 784-811 (1998)], in which
polarization emerges even though agents gather evidence about their beliefs,
and true belief yields a pay-off advantage. The key mechanism that generates
polarization involves treating evidence generated by other agents as uncertain
when their beliefs are relatively different from one's own.Comment: 22 pages, 5 figures, author final versio
Reliable Uncertain Evidence Modeling in Bayesian Networks by Credal Networks
A reliable modeling of uncertain evidence in Bayesian networks based on a
set-valued quantification is proposed. Both soft and virtual evidences are
considered. We show that evidence propagation in this setup can be reduced to
standard updating in an augmented credal network, equivalent to a set of
consistent Bayesian networks. A characterization of the computational
complexity for this task is derived together with an efficient exact procedure
for a subclass of instances. In the case of multiple uncertain evidences over
the same variable, the proposed procedure can provide a set-valued version of
the geometric approach to opinion pooling.Comment: 19 page
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