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KI-Net Conference Announcement

Kinetic theory for the emergence of complex behavior in social and economic systems

Feb 22 - 24, 2013

Arizona State University
Center for Social Dynamics and Complexity

Visitor Guide




Kinetic theory describes the stochastic interaction of many particles or agents via high dimensional evolution equations of probability densities. Computationally tractable, low dimensional equations for macroscopic observables (emergence) are obtained via asymptotics for large time scales and many agents. This follows the recipe of Boltzmann's kinetic gas theory, leading to the basic equations of gas dynamics in the limit.
In the social science context, this methodology has been extended from simple
gas molecules to birds and fish to describe flocking, and to opinions to describe the evolution of rumors in a crowd. The main advantage of this theory is that in its core it is an accurate, analytic and explicit first principle theory and, when it works, it allows for an analytic description of Agent Based Simulations (ABS).  It may also be used to relate popular aggregate models like population models in the social sciences or diffusion models in economy to their microscopic origins.
Applying such methods in biology is well within the experience of most applied mathematicians - they typically know physics and therefore have an idea what the interesting questions for a fish swarm are. This is less the case for simulation models in social science and economics. As a result, mathematical applications in social sciences are often not very relevant and seem to be staying at a descriptive qualitatitve level.  In essence the theory for emergent social phenomena is just emerging and the relationship between model, their purpose  and data is unresolved. 


This workshop will bring together applied mathematicians, social scientists  and engineers to educate each other about:  

  • The most interesting and promising fields in social sciences and economics, their research questions and the possibilities and obstacles for a kinetic description.
  • The possibilities of an aggregate mathematical description of multi-agent simulations, its successes and its limitations.
  • The use of kinetic models in these disciplines - qualitative and quantitative models, their validation and their predictive power. 



Dieter ArmbrusterArizona State University, School of Mathematical and Statistical
Irene M. GambaUniversity of Texas at Austin,
Christian RinghoferArizona State University, School of Mathematical and Statistical


Athena AktipisArizona State University
Dieter ArmbrusterArizona State University
Benjamin ArmbrusterNorthwestern University
Brad ArmendtASU
Ron AskinArizona State University
Robert L. AxtellGeorge Mason University
Dirk BrockmannNorthwestern University
Alina ChertockNorth Carolina State University
Gadi FibichTel Aviv University
Irene M. GambaUniversity of Texas at Austin
Andres Gomez-LievanoArizona State University
William GriffinArizona State University
Peter HelgessonChalmers University of Technology
Nicholas HohmanArizona State University
Reinhard IllnerUniversity of Victoria, Canada
Matthias KawskiASU
Karl KempfIntel Corporation
Eric KostelichArizona State University
Alexander KurganovTulane University
Dmitry KurochkinTulane University
Nicolas LanchierArizona State University
Yoonsang LeeUniversity of Texas at Austin
Yongki LeeUC Riverside
C. Dave LevermoreUniversity of Maryland
C. Dave LevermoreUniversity of Maryland
Doron LevyUniversity of Maryland
Hongmin LiArizona State University
Qin LiUniversity of Wisconsin-Madison
Liu LiuUniversity of Wisconsin-Madison
Hailiang LiuIowa State University
Jose LoboASU
Edward MacKerrowLos Alamos National Laboratory
Geoffrey McGregorUniversity of Victoria
Sébastien MotschArizona State University
Dawan MustafaChalmers University of Technology
Vladislav PanferovCalifornia State University, Northridge
Dimitrios PapadimitriouUGent
Theodore P. PavlicArizona State University
Christian RinghoferArizona State University
Juan D. RodriguezUniversity of Texas at Austin
David SirokyASU
Ravi SrinivasanThe University of Texas at Austin
Ilyssa SummerArizona State University
Milind TambeUniversity of Southern California
Changhui TanRice University
Andrea ThatcherArizona State University
Vladislav VysotskyASU
Bernt WennbergChalmers University, Göteborg, Sweden
Hui YuIowa State University
Na ZhangSchool of Human Evolution and Social Change


A limited amount of travel and local lodging is available for researchers in the early stages of their career who want to attend the full program, especially for graduate students and post-doctoral fellows.


Visitor Guide

Center for Social Dynamics and Complexity
Main Office-Room 412
Interdisciplinary Science and Technology Building 1
Arizona State University
Tempe, AZ




Funding provided by the NSF through the KI-net Grant.