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 ...
Informational Macrodynamics (IMD) presents a unified informational systemic approach with common information language for modeling, analysis and optimization of a variety of inter...
A regional transportation system and the movement of large traffic volumes through it, are characteristic of stochastic systems. The standard traffic management or transportation ...
ABSTRACT: This work considers the problem of performing a set of N tasks on a set of P cooperating message-passing processors (P N). The processors use a group communication servi...
This paper discusses the design, development, and use of a performance monitoring tool for Distributed Interactive Simulations (DIS). A typical DIS environment consists of hundred...