A process for anticipating and shaping adversarial behavior

Naval Research Logistics

Volumn 58, Issue 3, 2011, Pages 255-280

  McKay, Shawn C ^a   Chaturvedi, Alok ^b   Adams, Douglas E ^c  

^a Simulex Inc   (United States)

^b PURDUE UNIVERSITY   (United States)

^c PURDUE UNIVERSITY   (United States)

Author keywords

anticipate and shape; comprehensive approach; military operations research; SEAS

Indexed keywords

ACROSS TIME; AFGHANISTAN; ANTICIPATE AND SHAPE; COALITION FORCES; COMPREHENSIVE APPROACH; EMERGENT PHENOMENON; NEW APPROACHES; PARTIAL CONTROL; SEAS; TALIBAN; THIRD PARTIES;

MILITARY OPERATIONS; OPERATIONS RESEARCH;

FORECASTING;

EID: 79953062365     PISSN: 0894069X     EISSN: 15206750     Source Type: Journal    
DOI: 10.1002/nav.20440     Document Type: Article

References (47)

1. N. Beck, G. King, and, L. Zeng, Improving quantitative studies of international conflict: A conjecture, Am Polit Sci Rev, 94, 2000, 21-36.
2. B. Bell, E. Santos, and, S. M. Brown, "Making adversary decision modeling tractable with intent inference and information fusion", in: Proceedings of the 11th Conference on Computer Generated Forces and Behavioral Representation, Orlando, FL, 2002.
3. J. Bond, V. Petroff, S. O'Brien, and, D. Bond, "Forecasting turmoil in Indonesia: An application of hidden Markov models", Annual Conference of the International Studies Association, Montreal, Quebec, March 17-20, 2004.
4. E. Bossé, J. Roy, and, S. Wark, Concepts, models, and tools for information fusion, Artech House, Inc, Boston, 2007.
5. C. A. Bouman, Cluster: an unsupervised algorithm for modeling Gaussian mixtures, School of Electrical Engineering, Purdue University, Available at:, accessed on 2 July 2008.
6. P. T. Brandt, and, J. R. Freeman, Moving mountains: Bayesian forecasting as policy evaluation, Presented at the 2002 Meeting of the Midwest Political Science Association, Chicago, Il, April 2002.
7. R. Chandrasekaran, Troops face new tests in Afghanistan,Washington Post, 2009, Available at:, accessed on March 14, 2009.
8. A. R. Chaturvedi, D. Dolk, R. Chaturvedi, M. Mulpuri, D. Lengacher, S. Mellema, P. Poddar, C. Foong, and, B. Armstrong, Agent-based computational model of a virtual international system, Proc. of the Conference on Agent 2004,Chicago IL, 2004.
9. R. Chaturvedi, S. Mellema, A. R. Chaturvedi, M. Mulpuri, and, G. Pinczuk, Continuous validation framework: A case study of SEAS and Afghanistan, I/ITSEC, 2008.
10. D. J. Clark, Col,., The vital role of intelligence in counterinsurgency operations, United States Army War College, Research Paper (March 2006), pp. 1-25
11. H. Cooper, No time to go wobbly, Washington Times, 15 January 2008
12. J. B. Cruz, M. A. Simaan, A. Gacic, H. Jiang, B. Letellier, and, M. Li, "Modeling and control of military operations against adversarial control", Proceedings of the 39th IEEE Conference on Decision and Control, Sydney, Australia, 2000.
13. E. Doyle, L. McKaniel, and, S. Hardest, Countering irregular threats: A comprehensive approach,June 14, 2006, Available at:, accessed on 15 August 2008.
14. E. Edelman, A comprehensive approach to modern insurgency: Afghanistanand beyond, March 27, 2007, Available at:, accessed on 17 August 2008.
15. W. Enders, and, T. Sandler, The effectiveness of antiterrorism policies: A vector-autoregression- intervention analysis, Am Polit Sci Rev, 87, 1993, 829-844.
16. W. Enders, and, T. Sandler, After 9/11: Is it all different now? J Conflict Resolut, 49, 2005, 259-277.
17. J. Espinosa, J. Vandevalle, and, V. Wertz, Fuzzy logic, identification and predictive control, Springer, London, England, 2005.
18. G. Franklin, L. D. Powell, and, M. L. Workman, Digital control of dynamic systems, 2nd ed., Addison-Wesley Publishing Company, Massachusetts, 1990.
19. J. R. Freeman, J. T. Williams, and, L. Tse-min, Vector autoregression and the study of politics, Am J Polit Sci, 33, 1989, 824-877.
20. D. A. Gilmour, J. P. Hanna, W. E. MeKeever, Jr., and, M. J. Walter, "Real-time course of action analysis", in: Proceedings of the 10th International Command and Control Research and Technology Symposium, Cambridge, UK, 2005.
21. D. A. Gilmour, and, W. E. McKeever, High performance computing for real-time course of action analysis, AFRL Technical Report RI-RS-TR-2007-273, Rome, New York, 2008.
22. G. C. Goodwin, S. F. Graebe, and, M. E. Salgado, Control system design, Prentice Hall, New Jersey, 2001.
23. D. J. Hughes, (Editor), Moltke on the art of war: selected writings, Presidio Press, New York, NY, 1993.
24. J. Jelinek, and, D. Goodbole, "Model predictive control of military operations", Proc. 39th IEEE CDC,Sydney, 2000, 2562-2567. (Pubitemid 32528420)
25. Z. Maj Jobbagy, Literature survey on effects-based operations,A Ph. D. study on measuring military effects and effectiveness, TNO-FEL, FEL-03-B140, August 2003.
26. M. Kress, and, R. Azechtman, Why defeating insurgencies is hard: the effect of intelligence in counterinsurgency operationsâa best-case scenario, Oper Res, 57, 2009, 578-585.
27. L. Liao, D. Fox, and, H. Kautz, "Learning and inferring transportation routines", Proc. of the National Conference on Artificial Intelligence, San Jose, CA, 2004, 348-353.
28. L. Ljung, System identification theory for the user, Prentice Hall, Upper Saddle River, NJ, 1999.
29. T. W. Lucas, and, T. Turkes, Fitting Lanchester equations to the battles of Kursk and Ardennes, Nav Res Logist, 51, 2004, 95-116.
30. J. Maciejowski, Fault-tolerant aspects of model predictive control, IEEE Workshop on Model Predictive Control, IEEE, London, 1999.
31. J. Maciejowski, Predictive control with constraints, Prentice Hall, Essex, 2002.
32. The Mathworks, Inc., Model predictive control tool boxacent; Release Notes, Available at:, accessed on 30 August 2008.
33. S. A. McChrystal Gen, COMISAF'S initial assessment, Commander NATO International Security Assistance Force, Afghanistan, 30 Aug. 2009, Available at.
34. S. C. McKay, A control theory based hybrid architecture to anticipate and shape adversarial behavior, Dissertation, Purdue University, West Lafayette, IN, 2009.
35. T. Mockaitis, Winning hearts and minds in the 'war on terrorism', Small Wars & Insurgencies, 14, 2003, 21-38.
36. K. Ogata, Modern control engineering, 4th ed., Prentice Hall, New Jersey, 2002.
37. OneSAF Public Site, Available at:, accessed 30 July 2008.
38. C. H. Papadimitriou, and, K. Steiglitz, Combinatorial Optimization: algorithms and complexity, Prentice Hall, Englewood Cliffs, NJ, 1982.
39. M. H. Pesaran, D. Pettenuzzo, and, A. Timmermann, Forecasting time series subject to multiple structural breaks, Rev Econ Studies, 73, 2006, 1057-1084. (Pubitemid 44463521)
40. R. W. Pike, Optimization for engineering systems, Van Nostrand Reinhold Company, New York, 1986.
41. Planning joint operations, Joint publication 5-;4, published by Joint Chief of Staffs, 26 December 2006.
42. B. Presnell, R. Houlette, and, D. Fu, "Making behavior modeling accessible to non-programmers: challenges and solutions", Interservice/Industry Training, Simulation, and Education Conference, Orlando, FL, 2007.
43. J. Rainwater, The war in Afghanistan and better approaches to ending terrorism, The Seminal, 13 January 2009.
44. J. Risen, Poppy fields are now a front line in Afghan war, The New York Times, May 16, 2007.
45. W. Sexton < III, and, J. P. Stucklen, Dynamic course of action decision tool, AFRL Technical Report IF-RS-TR-2006-12, Rome, NY, 2006.
46. J. Salerno, M. Hinman, D. Boulware, and, P. Bello, "Information Fusion for situational awareness", Proceedings of the 6th International Conference of Information Fusion, 2003.
47. L. Tesfatsion, Handbook of computational economics agent-based computational economics, L. Tesfatsion, and, K. L. Judd, (Editors), Agent-based computational economics: A constructive approach to economic theory, in, North-Holland, Amsterdam, 2006, 831-880.