Fundamentals of Combat Modeling

Course Description

Combat, or conflict, modeling has a long history of being used by government and military organizations to explore the potential impact, effectiveness and/or efficiency of different proposed courses of action. Examine how modelers develop combat or conflict models and how the results are used.

Course ID: DEF 4011P
Course Format: Classroom

Available Classroom Sections

There are no available sections for this course. Please check back later.

View previous sections
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CRN Start date End date Format Location Cost
14446 Sep 9, 2014 Sep 11, 2014 Classroom Quantico, Virginia $1,195
15200 Oct 13, 2015 Oct 15, 2015 Classroom Quantico, Virginia $1,195
16055 Nov 17, 2015 Nov 19, 2015 Classroom Quantico, Virginia $1,195
18353 Mar 6, 2018 Mar 8, 2018 Classroom Quantico, Virginia $1,195

Special Discounts

GTRI employees are eligible for a discount on this course.  If you are a GTRI employee, please go to and look under “GT Professional Development” for a coupon code to use when checking out.

Note: Coupon codes must be applied during checkout and cannot be redeemed after your checkout is complete. Only one coupon code can be used per shopping cart.

Who Should Attend

Modelers, wargamers and programmers

How You Will Benefit

  • Know the history, philosophy and principles of combat modeling and simulation.

  • Understand the issues involved in the validation, verification and accreditation of combat or conflict models.

  • Describe the differences between deterministic and Monte Carlo models, their structure and operation and the implications of their results.

  • Explore issues involved with building combat models related to assumptions, variable instantiation and data validation.

  • Examine the environment you wish to model, choose a suitable modeling strategy and explain/defend your choice.

  • Assess the strengths and weaknesses of the DIME on PMESII modeling example presented in class.


  • Introduction to combat modeling
  • Lab and analysis: Richthofen’s War
  • Deterministic models
  • Monte Carlo models
  • Validation and verification
  • DIME on PMESII models
  • Randomness and random number generators

For Course-Related Questions

Please contact the course administrator: Charles Turnitsa