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A neural network trained to select aircraft maneuvers during air combat: a comparison of network and rule based performance

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1 Author(s)

Research to develop a neural network model that selects aircraft maneuvers in the domain of air-combat maneuvering is described. A methodology for converting rule-based systems into a neural network was established. A comparison between the neural network and a rule-based expert system was undertaken. Differences between the architectures were explored, and hypotheses as to causes of differential performance were made. Both models were compared with expert fighter pilots on a transfer task. The neural network agreed with maneuver selections made by expert fighter pilots 2.5 times more often than the rule-based system. These findings were explained in terms of the ability of neural nets to generalize maneuver selections to novel airspace conditions. Implications of these results were also discussed

Published in:

Neural Networks, 1990., 1990 IJCNN International Joint Conference on

Date of Conference:

17-21 June 1990