Stochastic Timed Influence Nets
Zhu Yan-guang, Lei Yong-lin · 2010
The existing Timed Influence Nets (TIN) framework is assumed that delays on arcs are constant. This constraint may turn out to be unrealistic in many real world situations. The proposed parametric enhancements would overcome the above limitation, and enable a system modeler to specify stochastic delay in a dynamic uncertain situation that the existing TIN fails to capture. The new class of models is named Stochastic Timed Influence Nets (STIN). Both TIN and STIN provide an easy-to-read and compact representation to several time-based probabilistic reasoning paradigms.