Abstract Discrete Bayesian Belief Network (BBN) has become a popular method for the
analysis of complex systems in various domains of application. One of its pillar is the …

Credal networks generalize Bayesian networks to allow for imprecision in probability values.
This paper reviews the main results on credal networks under strong independence, as …

Despite increasing collection efforts of empirical human reliability data, the available
databases are still insufficient for understanding the relationships between human errors …

Safety risk assessment of metro construction is necessary to prevent catastrophic accidents
that may cause heavy financial losses and casualties. In this paper, we introduce a …

Credal nets are probabilistic graphical models which extend Bayesian nets to cope with sets
of distributions. An algorithm for approximate credal network updating is presented. The …

Bayesian Networks are a flexible and intuitive tool associated with a robust mathematical
background. They have attracted increasing interest in a large variety of applications in …

Credal networks generalize Bayesian networks by relaxing the requirement of precision of
probabilities. Credal networks are considerably more expressive than Bayesian networks …

An algorithm for approximate credal network updating is presented. The problem in its
general formulation is a multilinear optimization task, which can be linearized by an …

This paper presents a family of algorithms for approximate inference in credal networks (that
is, models based on directed acyclic graphs and set-valued probabilities) that contain only …

Abstract Human Reliability Analysis aims at identifying, quantifying and proposing solutions
to human factors causing hazardous consequences. Quantifying the influence of the human …