Modeling time-varying uncertain situations using Dynamic Influence Nets

Author Affiliation

Sajjad Haider is Full-time Faculty Member at Institute of Business Administration (IBA), Karachi

Faculty / School

Faculty of Computer Sciences (FCS)


Department of Computer Science

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Document Type


Source Publication

International Journal of Approximate Reasoning




Applied Mathematics | Artificial Intelligence and Robotics | Computer Sciences | Mathematics


This paper enhances the Timed Influence Nets (TIN) based formalism to model uncertainty in dynamic situations. The enhancements enable a system modeler to specify persistence and time-varying influences in a dynamic situation that the existing TIN fails to capture. The new class of models is named Dynamic Influence Nets (DIN). Both TIN and DIN provide an alternative easy-to-read and compact representation to several time-based probabilistic reasoning paradigms including Dynamic Bayesian Networks. The Influence Net (IN) based approach has its origin in the Discrete Event Systems modeling. The time delays on arcs and nodes represent the communication and processing delays, respectively, while the changes in the probability of an event at different time instants capture the uncertainty associated with the occurrence of the event over a period of time.

Indexing Information

HJRS - W Category, Scopus, Web of Science - Science Citation Index Expanded (SCI)

Publication Status