A distributed numerical approach for managing uncertainty in large-scale multi-agent systems

Abstract

Mathematical models of complex processes provide precise definitions of the processes and facilitate the prediction of process behavior for varying contexts. In this paper, we present a numerical method for modeling the propagation of uncertainty in a multi-agent system (MAS) and a qualitative justification for this model. We discuss how this model could 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. © 2009 Springer Berlin Heidelberg.