PIs: Anita Raja, Michael Klibanov (Math)
RAs: Niraj Mehta
Mathematical models of complex processes provide precise definitions of the processes and facilitate the prediction of process behavior for varying contexts. In this work, we study a numerical method for modeling the propagation of uncertainty in a multi-agent system (MAS) and a qualitative justification for this model. This model will help determine the effect of various types of uncertainty on different parts of the multi-agent system; facilitate the development of distributed policies for containing the uncertainty propagation to local nodes; and estimate the resource usage for such policies.
Anita Raja and Michael Klibanov, A Distributed Numerical Approach for Managing Uncertainty in Large-Scale Multi-Agent Systems Proceedings of LNAI Hot Topics Safety and Security in Multiagent systems: The Early Years, pp: 75-84, volume 4324, editors: M. Barley, H. Mouratidis, A. Unruh , D. Spears, P. Scerri, F. Massacci, 2009.
Michael V. Klibanov and Alexandre Timonov Carleman Estimates for Coefficient Inverse Problems and Numerical Applications, Brill Academic Publishers, VSP (Imprint Brill) (Utrecht, Boston), 2004,