Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
In this paper we explore the problems of storing and reasoning about data collected from very large-scale wireless sensor networks (WSNs). Potential worldwide deployment of WSNs f...
— In this paper, we present a novel approach to controlling a robotic system online from scratch based on the reinforcement learning principle. In contrast to other approaches, o...
Vulnerability discovery rates need to be taken into account for evaluating security risks. Accurate projection of these rates is required to estimate the effort needed to develop ...
This paper proposes a simulation-based methodology for validation of a system under design in an early phase of development. The key element of this approach is the visual speciï¬...