Emerging Techniques and Tools



International interventions require unconventional approaches to modeling and analysis. According to Alberts et al. (2007, p. 5), the characteristics of intervention problems include:
  1. 1.
    The number and diversity of the participants is such that
    1. (a)

      There are multiple interdependent lines of management and control,

    2. (b)

      The objective functions of the participants conflict with one another or their components have significantly different weights, or

    3. (c)

      The participants’ perceptions of the situation differ in important ways; and

  2. 2.
    The effects space spans multiple domains and there is
    1. (a)

      A lack of understanding of networked cause-and-effect relationships, and

    2. (b)

      An inability to predict effects that are likely to arise from alternative plans of action.



Virtual World Bayesian Network Model Modeling Paradigm Underground Economy Computational Modeling Approach 


  1. Alberts, D., & Hayes, R., DoD Command and Control Research Program. (2007). Planning: Complex Endeavors. Washington, DC: CCRP Publications.Google Scholar
  2. Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton, NJ: Princeton University Press.Google Scholar
  3. Baker, J. A. III, & Hamilton, L. H. (2006). The Iraq Study Group Report. New York, NY: Vintage Publications.Google Scholar
  4. Banks, J., Carson, J., Nelson, B., & Nicol, D. (2004). Discrete-Event System Simulation (4th ed.). New York, NY: Prentice-Hall.Google Scholar
  5. Bankes, S. C. (2002). Tools and techniques for developing policies for complex and uncertain systems. Proceedings of the National Academy of Sciences, 99, 7263–7266.CrossRefGoogle Scholar
  6. Bigelow, J., & Davis, P. K., RAND Corporation. (2003). Implications for Model Validation of Multiresolution Modeling. Santa Monica, CA: RAND.Google Scholar
  7. Covey, J., Dziedzic, M., & Hawley, L. (eds.) (2005). The Quest for Viable Peace: International Intervention and Strategies for Conflict Transformation, Washington, DC: U.S. Institute of Peace Press.Google Scholar
  8. Davis, P. K, & Anderson, R. A., RAND Corporation. (2004). Improving the Composability of Department of Defense Models and Simulations (MG-101-OSD). Santa Monica, CA: RAND Distribution Services.Google Scholar
  9. Department of Defense. (1994). Modeling and Simulation (M&S) Management (DoD Directive 5000.59).Google Scholar
  10. Epstein, J. M., & Axtell, R. (1996). Growing Artificial Societies: Social Science from the Bottom Up. Cambridge, MA: MIT Press/Brookings Institution.Google Scholar
  11. Gleick, J. (1988). Chaos: Making a New Science. New York, NY: Penguin Books.Google Scholar
  12. Jervis, R. (1997a). System Effects: Complexity in Political and Social Life. Princeton, NJ: Princeton University Press.Google Scholar
  13. Jervis, R. (1997b). Complex Systems: The Role of Interactions. In: Alberts, D. S. & Czerwinski, T. J. (eds.), Complexity, Global Politics and National Security. Washington, DC: National Defense University.Google Scholar
  14. Lynn, J. A. (2005). Patterns of insurgency and counterinsurgency. Military Review, 85(4), 22–27.Google Scholar
  15. Manwaring, M. G., & Fishel, J. T. (1992). Insurgency and counterinsurgency: towards a new analytical approach. Small Wars & Insurgencies, 3(3), 272–305.CrossRefGoogle Scholar
  16. McCormick, G. H. (1999). People’s War. In: Ciment, J. (ed.), Encyclopedia of Conflicts Since World War II, Vol. I: Afghanistan Through Burundi. New York, NY: Schocken Press.Google Scholar
  17. Meilinger, P. (2004). The origins of effects based operations, Joint Forces Quarterly, 35, 116–122.Google Scholar
  18. Office of the Director of National Intelligence (2007). Prospects for Iraq’s Stability: A Challenging Road Ahead. (National Intelligence Estimate). Available at www.dni.gov/press_releases/20070202_release.pdf.
  19. Pearl, J. (2000). Causality: Models, Reasoning, and Inference. Cambridge, MA: Cambridge University Press.MATHGoogle Scholar
  20. Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World, New York, NY: McGraw Hill Publishing.Google Scholar
  21. Taylor, G., Bechtel, R., Morgan, G., & Waltz, E. (2006). A Framework for Modeling Social Power Structures. Proceedings of Conference of the North American Association for Computational Social and Organizational Sciences. Notre Dame, IN.Google Scholar
  22. U.S. Army. (2006). Counterinsurgency (Field Manual FM 3-24, MCWP 3-33.5). Washington, DC: Department of the Army.Google Scholar
  23. Walker, D. M., Comptroller General of the United States, Government Accounting Office (GAO). (2006). Stabilizing Iraq: An Assessment of the Security Situation. (Statement for the Record, GAO-06-1094T). Author.Google Scholar
  24. Waltz, E. (2006). Means and Ways: Practical Approaches to Impact Adversary Decision-Making Processes. In: Kott, A. (ed.), Information Warfare and Organizational Decision-Making. Boston, MA: Artech Press.Google Scholar
  25. Waltz, E. (2008). Situation Analysis and Collaborative Planning for Complex Operations. Proceedings of the 13th International Command and Control Research Symposium. Bellevue, WA.Google Scholar
  26. Zacharias, G., MacMillan, J., & Van Hemel, S. B. (eds.) (2008). National Research Council. Behavioral Modeling and Simulation: From Individuals to Societies. Washington, DC: National Academies Press.Google Scholar

Copyright information

© Springer US 2010

Authors and Affiliations

  1. 1.Intelligence Innovation DivisionBAE Systems Advanced Information TechnologiesAnn ArborUSA

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