Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Directed model checking algorithms focus computation resources in the error-prone areas of concurrent systems. The algorithms depend on some empirical analysis to report their per...
We apply the symbolic analysis principle to pushdown systems. We represent (possibly in nite) sets of con gurations of such systems by means of nite-state automata. In order to re...
We describe a general model for embedding object-oriented constructs into calculi of mobile agents. The model results from extending agents with methods and primitives for message ...
Abstract--This paper presents a full state feedback adaptive dynamic inversion method for uncertain systems that depend nonlinearly upon the control input. Using a specialized set ...