The paper presents an efficient solution to decision problems where direct partial information on the distribution of the states of nature is available, either by observations of ...
Bayesian implicative analysis was proposed for summarizing the association in a 22 contingency table in terms possibly asymmetrical such as, e.g., presence of feature a implies, i...
A Chaotic Probability model is a usual set of probability measures, M, the totality of which is endowed with an objective, frequentist interpretation as opposed to being viewed as...
I introduce and study a fairly general imprecise secondorder uncertainty model, in terms of lower desirability. A modeller's lower desirability for a gamble is defined as her...
Probabilistic logic programming is a powerful technique to represent and reason with imprecise probabilistic knowledge. A probabilistic logic program (PLP) is a knowledge base whi...