What does congestion spreading have in common with cascading disaster spreading? How can one characterize the breakdown dynamics of traffic flows in urban networks? Why does the traffic situation vary largely from one day to another, even when the travel demands are almost the same? What variables would allow better prediction of the severity of developing traffic congestion? Can models of self-organized criticality or percolation provide additional insights into the size distribution of congestion events? How vulnerable is the critical infrastructure "transportation network"? How does the sensitivity of traffic flows to local perturbations (such as accidents) depend on the network topology? We are planning to respond to these challenges with a series of models that capture grid lock events, integration of self-organized signal control, cascading congestion events, and mental maps of activity generation in traffic systems.

Why do wars occur? How can they be ended, or even better, entirely prevented? What are the social consequences of such disruptions? Although the risk and intensity of political violence has been declining since the mid-1990s, civil wars, terrorism, and other types of conflict still represent a considerable risk in many parts of the world. We propose a new approach to conflict research that is based on the principles of non-equilibrium theory. Our goal is to achieve a conceptual breakthrough by viewing conflict as a dynamical process rather than as an isolated event caused by static conditions. There are several reasons why such an approach promises to break new ground. First, by adopting an explicitly systemic perspective, the researcher can avoid artificial ceteris-paribus assumptions. Second, the actors and their interactions can be dynamically modeled, including their identities and boundaries. Finally, conflict can be viewed as a non-equilibrium phenomenon that results from a dynamic process when the system transits from one meta-stable state to another.