A neural-network based behavioral theory of tank commanders

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Author
Bui, Tung X.
Dryer, David A.
Laskowski, Matthew Ludwig
Date
1992-05Metadata
Show full item recordAbstract
Based on the presumption that data observed in high-tech and fast changing battles do have some
intrinsic richness to them that synthetic modelling fails to capture, we contend that data induction
techniques can be successfully used to generalize combat behaviors. This paper reports the use of
neural networks as a computer-based adaptive induction algorithm to understand and uncover ground
combat behaviors. Experiments with neural networks using tank movement data from the National
Training Center (NTC), Fort Irwin, demonstrate that a two-dimensional cognitive map of closely task
organized units can be derived. The findings seem to confirm our behavioral theory that tank
commanders (i) are mission-driven, (if) act as an integral part of their platoon, (iii) perform sequential
decision making to determine their next moves, and (iv) when isolated, extemporaneous behaviors may
take precedence over normative gorup behavior. Once trained, a neural-network based model of
closely task organized units can be used to predict the itinerary sequences of a tank given its initial geographic position.
NPS Report Number
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