Skip to main content

Gaming and Simulating Ethno-Political Conflicts

  • Chapter
  • First Online:
Computational Methods for Counterterrorism

Summary

This chapter begins by describing a universally recurring socio-cultural “game” of inter-group competition for control of resources. It next describes efforts to author software agents able to play the game as real humans would - which suggests the ability to study alternative ways to influence them, observe PMESII effects, and potentially understand how best to alter the outcomes of potential conflict situations. These agents are unscripted, but use their decision making to react to events as they unfold and to plan out responses. For each agent, a software called PMFserv operates its perception and runs its physiology and personality/value system to determine fatigue and hunger, injuries and related stressors, grievances, tension buildup, impact of rumors and speech acts, emotions, and various collective and individual action decisions. The chapter wraps up with a correspondence test from a SE Asian ethnic conflict, the results of which indicate significant correlation between real and agentbased outcomes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Bharathy, G. K. (2006) Agent Based Human behavior Modeling: A Knowledge Engineering Based Systems Methodology for Integrating of Social Science Frameworks for Modeling Agents with Cognition, Personality & Culture. (Doctoral dissertation, University of Pennsylvania, July 2006)

    Google Scholar 

  • Damasio, A. R. (1994). Descartes’ Error: Emotion, Reason, and the Human Brain. New York: Avon.

    Google Scholar 

  • De Marchi, S. (2005). Computational and Mathematical Modeling in the Social Sciences. Cambridge: Cambridge University Press.

    Google Scholar 

  • Epstein, J., Steinbruner, J. D., Parker, M. T. (2001), Modeling civil violence: An agent-based computational approach. Proceedings of the National Academy of Sciences. Washington DC: Brookings (CSED WP#20).

    Google Scholar 

  • Green, K. C. (2002). Forecasting decisions in conflict situations: a comparison of game theory, role-paying, and unaided judgement. International Journal of Forecasting, 18, 321–344.

    Article  Google Scholar 

  • Hermann, M. G. (1999). Assessing Leadership Style: A Trait Analysis. Hilliard, OH: Social Sci. Automation, Inc.

    Google Scholar 

  • Heuer, R. J., Jr. (1999). Psychology of Intelligence Analysis. Washington, DC: Center for the Study of Intelligence, Central Intelligence Agency.

    Google Scholar 

  • House, R. J. Hanges, P. J., Javidan M, et al. (2004), Culture, Leadership, and Organizations: The GLOBE Study of 62 Societies. Thousand Oaks, CA: Sage Publications

    Google Scholar 

  • Johns, M., Silverman, B. G. (2001). How emotion and personality effect the utility of alternative decisions: A terrorist target selection case study.Proceedings of the 10th CGF & BR, SISO. Norfolk, Virginia.

    Google Scholar 

  • Johns, M. (2006) Deception and Trust in Complex Semi-Competitive Environments. Doctoral dissertation, University of Pennsylvania.

    Google Scholar 

  • Maoz, I., Eidelson, R. J. (2007). Psychological bases of extreme policy preferences: How the personal beliefs of Israeli Jews predict their support for population transfer in the Israeli-Palestinian conflict. American Behavioral Scientist, 50, 1476–1497.

    Article  Google Scholar 

  • Ortony, A., Clore, G. L., Collins, A. (1988). The Cognitive Structure of Emotions. Cambridge: Cambridge University Press.

    Google Scholar 

  • Pew, R. W., Mavor, A. S. (1998). Modeling Human and Organizational Behavior: Application to Military Simulation. Washington, DC: National Academy Press.

    Google Scholar 

  • Silverman, B. G., Johns, M., Weaver, R., O’Brien, K., Silverman, R. (2002a). Human behavior models for game-theoretic agents. Cognitive Science Quarterly, 2(3/4), 273–301.

    Google Scholar 

  • Silverman, B. G., Johns, M., O’Brien, K., Weaver, R., Cornwell, J. (2002b). Constructing virtual asymmetric opponents from data and models in the literature: Case of crowd rioting. Proceedings of the 11th Conference on Computer Generated Forces and Behavioral Representation, Orlando, Florida, 97–106.

    Google Scholar 

  • Silverman, B. G. (2005). Human performance simulation. In J. Ness, D. Ritzer, V. Tepe (Eds.), The Science and Simulation of Human Performance (Chapter 9). New York: Elsevier.

    Google Scholar 

  • Silverman, B. G., Rees, R, et al. (2005, May), Athena’s prism: A diplomatic strategy role playing game for generating ideas and exploring alternatives. Proceedings of the Internat’l Conference on Intelligence Analysis, MacLean, VA: Mitre.

    Google Scholar 

  • Silverman, B. G., Johns, M., Cornwell, J., O’Brien, K. (2006a). Human behavior models for agents in simulators and games: Part I enabling science with PMFserv. Presence , v. 15: 2 April.

    Google Scholar 

  • Silverman, B. G., Bharathy, G.K., O’Brien, K., Cornwell, J. (2006b). Human behavior models for agents in simulators and games: Part II gamebot engineering with PMFserv. Presence, v. 15: 2, April.

    Google Scholar 

  • Silverman, B. G., Bharathy, G. K., Johns, M., Nye, B., Eidelson, R., Smith, T., Socio-Cultural Games for Training and Analysis. Tech Report avail from the authors (submitted for publication 2006c).

    Google Scholar 

  • Wood, E. J. (2003). Modeling Robust Settlements to Civil War: Indivisible Stakes and Distributional Compromises. Santa Fe, Unpublished Paper. Available from the author: wood@santafe.edu

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Silverman, B.G., Bharathy, G.K., Nye, B.D. (2009). Gaming and Simulating Ethno-Political Conflicts. In: Argamon, S., Howard, N. (eds) Computational Methods for Counterterrorism. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01141-2_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-01141-2_15

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01140-5

  • Online ISBN: 978-3-642-01141-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics