NetSE: Small: Complex Adaptive Networks: Generative Models and Statistical Analysis

University Of Southern California, Los Angeles CA

Investigators

Abstract

Our society is becoming increasingly dependent on various technological networks, such as transportation systems, electrical power?distribution grids, computer networks, and so on. As those networks evolve and grow in complexity, their dynamical behavior is becoming difficult to understand and predict. This project will develop a general framework for modeling growth and evolution of such complex adaptive networks, based on the notion of interacting stochastic processes. The intuition behind this approach is that the interactions that form the network are informed by the collective state of the stochastic processes, while those processes themselves are affected by the forming network structure. The presence of such a feedback mechanism is vital for capturing realistic behavior of many real-world networks. The research will develop rigorous mathematical methods for analyzing structural and dynamical properties of adaptive networks, and define novel information?theoretic measures for quantifying their complexity. Broader Impact: Our nation?s technological infrastructure of future will depend on our ability to control large?scale, dynamic networks of interconnected heterogeneous entities. This work will help to better understand, characterize, and predict the collective behavior of such networks. The project will train new professionals and scientists in an important interdisciplinary area, and develop a graduate course material on complex adaptive networks.