Data envelopment analysis (DEA) has been proven as an efficient technique to evaluate the performance of homogeneous decision making units (DMUs) where multiple inputs and outputs exist. In the conventional applications of DEA, the data are considered as specific numerical values with explicit designation of being an input or output. However, the observed values of the data are sometimes imprec...

We propose a decision procedure, i.e. an inference system for clauses containing rigid and flexible variables. Rigid variables are only allowed to have one instantiation, whereas flexible variables are allowed as many instantiations as desired. We assume a set of clauses containing only rigid variables together with a set of clauses containing only flexible variables. When the flexible clauses ...

When modelling a probability distribution with a Bayesian network, we are faced with the problem of how to handle continuous variables. Most previous works have solved the problem by discretizing them with the consequent loss of information. Another common alternative assumes that the data are generated by a Gaussian distribution (parametric approach), such as conditional Gaussian networks, wit...

A unification procedure for a theory with individual and sequence variables, free constants, free fixed and flexible arity function symbols and patterns is described. The procedure enumerates a set of substitution/constraint pairs which constitutes the minimal complete set of unifiers.