OA4607 Tactical Decision Making

This course deals with computer-aided decision making. Topics include the human-computer interface, the construction of effective graphics, verification/validation, and theoretical frameworks for competitive and non-competitive decision making. Kalman filters are introduced as an important fusion and tracking tool. The primary classroom application areas are information fusion, search/track and mine warfare. A project is required.

Prerequisite

OS2103 or equivalent, and a working knowledge of a programming language such as R, MATLAB, or Python.

Lecture Hours

4

Lab Hours

0

Course Learning Outcomes

Upon successful completion of this course, you should be able to:
• Examine the tradeoff between force size and fighting effectiveness.
• Solve advanced Lanchester Models numerically.
• Estimate a target’s location based on noisy measurements (e.g., lines of bearings).
• Utilize Kalman Filter techniques to track a target.
• Assess battlefield damage based on number of shots fired, with and without feedback.
• Define and compute mine warfare MOEs such as simple initial threat, catastrophe probability, casualty distribution, and threat profile.
• Describe the shortcomings with various mine warfare models and why it is inherently difficult to effectively model mine warfare analytically.
• Solve sequential and simultaneous zero sum games.