This paper proposes a systematized presentation and a terminology for observations in a
Bayesian network. It focuses on the three main concepts of uncertain evidence, namely …

In this paper we describe architecture and implementation of a Probabilistic Agent-Based
Intrusion Detection (PAID) system. The PAID system has a cooperative agent architecture …

Possibilistic networks, which are compact representations of possibility distributions, are
powerful tools for representing and reasoning with uncertain and incomplete information in …

Conditioning, belief update and revision are important tasks for designing intelligent
systems. Possibility theory is among the powerful uncertainty theories particularly suitable …

This paper aims to get a better understanding of the notions of evidence, probabilistic
evidence and likelihood evidence in Bayesian Networks. Evidence comes from an …

The acquisition of knowledge is no longer enough to succeed in a society characterized by a
constant change and high levels of uncertainty. Accordingly, universities have increasingly …

In this paper we analyze the performance of three algorithms for soft evidential update, in
which a probability distribution represented by a Bayesian network is modified to a new …

Abstract The objective of Smart Manufacturing is to improve productivity and
competitiveness in industry, based on in-process data. It requires reliable, explainable and …

Evidence in a Bayesian network comes from information based on the observation of one or
more variables. A review of the terminology leads to the assessment that two main types of …

Dans un réseau bayésien, une observation sur une variable signifie en général que cette
variable est instanciée. Ceci signifie que l'observateur peut affirmer avec certitude que la …