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Representing the command and control process in simulation models of conflict

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  • J Moffat

    (DERA)

Abstract

Command and Control is the process by which military personnel in war command their forces to take account of military aims and objectives. Across NATO, there is a growing realisation that the proper representation of Command and Control (C2) in models of conflict is very important. Since it essentially concerns itself with the representation of human decision-making, this is recognised as one of the most difficult areas for defence analysis. One approach to this problem is through the use of large rule-based expert systems. The work reported here lays out an alternative approach founded on the use of Bayesian inference and transitions between different mission ‘states’, leading to what we call the the mission based approach to Command and Control. These ideas are already being incorporated into the next generation of simulation models currently under development which range across the land/air, maritime and peacekeeping areas of application.

Suggested Citation

  • J Moffat, 2000. "Representing the command and control process in simulation models of conflict," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(4), pages 431-439, April.
    • Handle: RePEc:pal:jorsoc:v:51:y:2000:i:4:d:10.1057_palgrave.jors.2600889
    DOI: 10.1057/palgrave.jors.2600889
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    Citations

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    Cited by:

    1. L Dodd & J Moffat & J Smith, 2006. "Discontinuity in decision-making when objectives conflict: a military command decision case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(6), pages 643-654, June.
    2. J Medhurst & I Stanton & A Berry, 2010. "Risk taking by decision makers—using card-based decision gaming to develop models of behaviour," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(11), pages 1561-1571, November.
    3. Kalloniatis, Alexander C. & McLennan-Smith, Timothy A. & Roberts, Dale O., 2020. "Modelling distributed decision-making in Command and Control using stochastic network synchronisation," European Journal of Operational Research, Elsevier, vol. 284(2), pages 588-603.
    4. S Robinson & T Alifantis & J S Edwards & J Ladbrook & A Waller, 2005. "Knowledge-based improvement: simulation and artificial intelligence for identifying and improving human decision-making in an operations system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 912-921, August.
    5. Moffat, James & Medhurst, John, 2009. "Modelling of human decision-making in simulation models of conflict using experimental gaming," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1147-1157, August.
    6. J Moffat & I Campbell & P Glover, 2004. "Validation of the mission-based approach to representing command and control in simulation models of conflict," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(4), pages 340-349, April.
    7. J Medhurst & I M Stanton & H Bird & A Berry, 2009. "The value of information to decision makers: an experimental approach using card-based decision gaming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(6), pages 747-757, June.
    8. Robinson, Stewart, 2002. "General concepts of quality for discrete-event simulation," European Journal of Operational Research, Elsevier, vol. 138(1), pages 103-117, April.
    9. S Robinson, 2005. "Discrete-event simulation: from the pioneers to the present, what next?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 619-629, June.

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