The faculty and students within the Program have a diverse set of research interests focused around complex social systems, computational modeling and related techniques. The overall field has become known as Computational Social Science. Research areas include design science, economics, geography, geographical information systems (GIS), public policy, political science, network science, cognitive science, international relations and anthropology.

One of the main tools we use for our studies is that of agent-based modeling (Axtell, 2000) often utilizing our in-house multi-agent simulation toolkit: MASON (Luke et al., 2005).

Agent-based models have been developed to investigate a range of complex human and social systems from the bottom up, such as:

  • The rise and fall of civilizations both in Northern America (Axtell et al., 2002) and Inner Asia (Cioffi-Revilla et al., 2007) which are applicable to the rise of social complexity more generally (Cioffi-Revilla, 2005);
  • Computational economics (Axtell, 2007);
  • Tax compliance (Bloomquist, 2010);
  • Cultural dynamics and environmental change (Hailegiorgis et al., 2010);
  • Political instability and ecological dynamics in Eastern Africa (Kennedy et al., 2010a);
  • Design science (Saunders and Gero, 2001; 2002; and 2004; Sosa and Gero, 2002; 2005)
  • Conflict (Geller and Alam 2010; Geller et al., 2011; Gulden, 2002; Hendrey et al., 2010a; Latek et al., 2010);
  • Segregation (Crooks, 2010);
  • Cognitive modeling within agent-based models (Kennedy and Bugajska, 2010; Kennedy et al., 2010b; );
  • Design optimization (Gero and Peng, 2009);
  • The potential of ABM in virtual worlds (Crooks et al., 2009).

In addition we are constantly striving to solve some of the challenges in this field (e.g. Crooks et al., 2008) as well as building evidence-based models (e.g. Geller and Moss, 2008) which are quantitatively based (e.g. Mussavi Rizi et al., 2010).

Other work within the Program include power law analysis applied to conflict (e.g. Cioffi-Revilla and Pedro, 2009) and civil violence (e.g. Gulden, 2002), social network analysis (e.g. Tsvetovat and Carley, 2007; Tsvetovat and Łatek, 2009), coupling system-dynamics models with agent-based models (Geller and Alam, 2010) and using GPUs for large-scale agent-based models (Hendrey et al., 2010b).

Funding for this research comes from a variety of sources including the National Science Foundation, Office of Naval Research, Defense Advanced Research Projects Agency, Department of Defense and the research is channeled back into the courses that we offer.

Further research applying the diverse range of skills and expertise of faculty and students can be seen in the Center for Social Complexity.


Selected Publications:

  • Axtell, R. (2000), Why Agents? On the Varied Motivations for Agent Computing in the Social Sciences, Center on Social and Economic Dynamics (The Brookings Institute): Working Paper 17, Washington DC.
  • Axtell, R. (2007), 'What Economic Agents do: How Cognition and Interaction Lead to Emergence and Complexity', The Review of Austrian Economics, 20(2-3): 105-122.
  • Axtell, R., Epstein, J.M., Dean, J.S., Gumerman, G.J., Swedlund, A.C., Harburger, J., Chakravarty, S., Hammond, R., Parker, J. and Parker, M. (2002), 'Population Growth and Collapse in a Multiagent Model of the Kayenta Anasazi in Long House Valley', Proceedings of the National Academy of Sciences of the United States of America (PNAS), 99(3): 7275-7279.
  • Bloomquist, K. (2010), 'Tax Compliance as an Evolutionary Coordination Game: An Agent-Based Approach', Public Finance Review, (doi:10.1177/1091142110381640).
  • Cioffi-Revilla, C.(2012), 'Modeling and Simulation at the Mason Center for Social Complexity',The Voice of Technology,Winter 2012: 30-31.
  • You can download the paper here.

  • Cioffi-Revilla, C. and Goolsby, Rebecca, ONR (2011), 'Advanced Modeling Capability for Rapid Disaster Response', Innovation Beyond Imagination, Vol. 7, September 2011, 12-13.
  • You can download the paper here.

  • Cioffi-Revilla, C. (2010), 'Computational Social Science', Wiley Interdisciplinary Reviews: Computational Statistics, 2(3): 259-271.
  • Cioffi-Revilla, C. (2005), 'A Canonical Theory of Origins and Development of Social Complexity', Journal of Mathematical Sociology, 29(2): 1-21.
  • Cioffi-Revilla, C., Luke, S., Parker, D.C., Rogers, J.D., Fitzhugh, W.W., Honeychurch, W., Frohlich, B., De Priest, P. and Amartuvshin, C. (2007), 'Agent-Based Modeling Simulation of Social Adaptation and Long-Term Change in Inner Asia', in Takahashi, S., Sallach, D. and Rouchier, J. (eds.), Advancing Social Simulation: The First World Congress, Springer, Japan, pp. 189-200.
  • Cioffi-Revilla, C. and Pedro, R. (2009), 'Modeling Uncertainty in Adversary Behavior: Attacks in Diyala Province, Iraq, 2002-2006', Studies in Conflict and Terrorism, 32(3): 253-276.
  • Crooks, A.T. (2010), 'Constructing and Implementing an Agent-Based Model of Residential Segregation through Vector GIS', International Journal of GIS, 24(5): 661-675.
  • Crooks, A.T., Castle, C.J.E. and Batty, M. (2008), 'Key Challenges in Agent-Based Modelling for Geo-spatial Simulation', Computers, Environment and Urban Systems, 32(6): 417-430.
  • Crooks, A.T., Hudson-Smith, A. and Dearden, J. (2009), 'Agent Street: An Environment for Exploring Agent-Based Models in Second Life', Journal of Artificial Societies and Social Simulation, 12(4), Available at
  • Geller, A., Mussavi Rizi, S.M. and Łatek, M.M. (2011), 'How Corruption Blunts Counternarcotic Policies in Afghanistan: A Multiagent Investigation', in J. Salerno et al. (eds.), Social Computing, Behavioral Modeling, and Prediction, Lecture Notes in Computer Science 6589, Springer-Verlag, Berlin, Germany. pp. 121-128.
  • Geller, A. and Alam, S.J. (2010), 'A Socio-Political and -Cultural Model of the War in Afghanistan', International Studies Review, 12(1): 8-30.
  • Geller, A., Goolsby, R. and Hoffer, L. (2010), 'On Qualitative Data in Agent-Based Models', 3rd World Congress on Social Simulation: Scientific Advances in Understanding Societal Processes and Dynamics, University Of Kassel, Kassel, Germany.
  • Geller, A. and Moss, S. (2008), 'Growing Qawm: An Evidence-driven Declarative Model of Afghan Power Structures', Advances in Complex Systems, 11(2): 321-335.
  • Gero, J.S. and Peng, W. (2009), 'Understanding the Behaviours of a Situated Agent: A Markov Chain Analysis', Knowledge-Based Systems, 22(8): 610-621.
  • Gulden, T.R. (2002), 'Spatial and Temporal Patterns in Civil Violence: Guatemala, 1977-1986', Politics and the Life Sciences, 21(1): 26-36.
  • Hailegiorgis, A., Kennedy, W., Roleau, M., Bassett, J., Coletti, M., Balan, G. and Gulden, T. (2010), 'An Agent Based Model of Climate Change and Conflict among Pastoralists in East Africa', in Swayne, D.A., Yang, W., Voinov, A.A., Rizzoli, A.E. and Filatova, T. (eds.), 2010 International Congress on Evironmental Modelling and Software Modeling for Environment's Sake.
  • Hendrey, M., Kennedy, W. and Axtell, R. (2010a), 'Talibanization of Afghanistan: An Agent-based Model', 78th MORS Symposium, Quantico, VA.
  • Hendrey, M., Rouly, O. and Axtell, R. (2010b), 'Parallel Agent Execution for Large-Scale Models: New Results with GPUs', 78th MORS Symposium, Quantico, VA.
  • Kennedy, W.B., Hailegiorgis, A.B., Rouleau, M., Bassett, J.K., Coletti, M., Balan, G.C. and Gulden, T. (2010a), 'An Agent-Based Model of Conflict in East Africa And the Effect of Watering Holes', Behavior Representation in Modeling and Simulation (BRiMS) Conference, Charleston, SC.
  • Kennedy, W.G. and Bugajska, M. (2010), 'Integrating Fast and Slow Cognitive Processes', in Salvucci, D.D. and Gunzelmann, G. (eds.), Proceedings of the International Conference on Cognitive Modeling (ICCM 2010), Philadelphia, PA, pp. 121-126.
  • Kennedy, W.G., Ritter, F.E. and Best, B.J. (2010b), 'Behavioral Representation in Modeling and Simulation: Introduction to CMOT Special Issue—BRiMS 2009', Computational & Mathematical Organization Theory, 16(3): 217-219.
  • Łatek, M.M., Mussavi Rizi, S.M. and Geller, A. (2010), 'Persistence in the Political Economy of Conflict: The Case of the Afghan Drug Industry', AAAI Fall Symposium Series, Arlington, VA. pp. 86-92.
  • Luke, S., Cioffi-Revilla, C., Panait, L., Sullivan, K. and Balan, G. (2005), 'MASON: A Multi-Agent Simulation Environment', Simulation, 81(7): 517-527.
  • Mussavi Rizi, S.M., Łatek, M.M. and Geller, A. (2010), 'Merging Remote Sensing Data and Population Surveys in Large, Empirical Multiagent Models: The Case of the Afghan Drug Industry', 3rd World Congress on Social Simulation: Scientific Advances in Understanding Societal Processes and Dynamics, University Of Kassel, Kassel, Germany.
  • Sosa, R. and Gero, J. S. (2002), Cellular Automata Models of Creative Design Situations, in J.S. Gero, J.S. and Brazier, F. (eds), Agents in Design 2002, Key Centre of Design Computing and Cognition, University of Sydney, Australia, pp. 165-180.
  • Saunders, R. and Gero, J. S. (2004), Situated Design Simulations using Curious Agents, AIEDAM, 18 (2): 153-161
  • Saunders, R. and Gero, J. S. (2002), How to Study Artificial Creativity, in Hewett T. and Kavanagh, T. (eds.), Creativity and Cognition 2002, ACM Press, New York, NY, pp. 80-87.
  • Saunders, R. and Gero, J.S. (2001), Designing for Interest and Novelty: Motivating Design Agents, in de Vries, B., van Leeuwen J. and Achten H. (eds.), CAADFutures 2001, Kluwer, Dordrecht, pp.725-738.
  • Sosa, R. and Gero, J. S. (2005), ‘A Computational Study of Creativity in Design, AIEDAM, 19(4): 229-244.
  • Tsvetovat, M. and Carley, K.M. (2007), 'On effectiveness of wiretap programs in mapping social networks', Computational & Mathematical Organization Theory, 13(1): 63-87.
  • Tsvetovat, M. and Łatek, M.M. (2009), 'Dynamics of Agent Organizations: Application to Modeling Irregular Warfare', in Goebel, R., Siekmann, J. and Wahlster, W. (eds.), Multi-Agent-Based Simulation IX, Lecture Notes in Computer Science, Springer-Verlag, Berlin, Germany, pp. 60-70.