In many reliability studies based on data, reliability engineers face incompleteness and incoherency problems in the data. Probabilistic tools badly handle these kinds of problems...
Existing cognitive agent programming languages that are based on the BDI model employ logical representation and reasoning for implementing the beliefs of agents. In these programm...
Abstract— This paper deals with the use of Bayesian Networks to compute system reliability of complex systems under epistemic uncertainty. In the context of incompleteness of rel...
It is well known that among all probabilistic graphical Markov models the class of decomposable models is the most advantageous in the sense that the respective distributions can b...
This paper deals with the problem of inference under uncertain information. This is a generalization of a paper of Cardona et al. (1991a) where rules were not allowed to contain n...