Bayesian networks are probabilistic graphical models widely employed in AI for the implementation of knowledge-based systems. Standard inference algorithms can update the beliefs a...
— This paper addresses the exact transformation of nonlinear systems into a multiple model form with unmeasurable premise variables. The multiple model structure serves to treat ...
This research examines the performance of CONWIP versus "push" workload control in a simple, balanced manufacturing flowline. Analytical models and simulation experiment...
Abstract. The paper presents methods for model checking a class of possibly infinite state concurrent programs using various types of bi-simulation reductions. The proposed method...
Tiling systems that recognize two-dimensional languages are intrinsically non-deterministic models. We introduce the notion of deterministic tiling system that generalizes determin...