Predicting and Controlling Systems of Interdependent Networks: Exploiting Interdependence for Control
MURI Topic: Controlling Collective Phenomena in Complex Networks
UC Davis news article on our team, Sept 2013

Research Team
  • Raissa M. D'Souza (PI), UC Davis
  • Jim Crutchfield, UC Davis
  • Leonardo Duenas-Osorio, Rice University
  • Mehran Mesbahi, University of Washington
  • Michael Roukes, California Institute of Technology
  • Brenda McCowan Lab, UC Davis

  • Research Problem & Technical Approach
    Collections of networks are at the core of military and civilian life, spanning technological, biological and social systems. All of these networks interact, leading to new emergent properties and unanticipated phase transitions and vulnerabilities. We will develop rigorous principles to predict and control behaviors of systems made of interdependent networks. Our highly interdisciplinary approach synthesizes mathematical theories from statistical physics, control theory, nonlinear dynamics, game theory, information theory, system reliability theory, and operations research. The results will be informed and validated by empirical studies of real-world systems from nanoscale mechanical oscillators, to collections of interdependent critical infrastructure systems, to data on coalitions and conflict in primate societies, to longitudinal data on the evolution of political networks of nation states and task-oriented social networks in Open Source Software. Our focus is to develop new approaches that exploit network interdependence for network control, and this diversity of empirical testbeds is central to developing robust theoretical principles and widely applicable methods.

    Anticipated Funding and Duration
    $6.25 million, Fall 2013-Summer 2018.
    We anticipate hiring several talented PhD students and postdocs.