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Summary: Behavioral Cloning of Student Pilots with Modular Neural Networks
Charles W. Anderson anderson@cs.colostate.edu
Department of Computer Science, Colorado State University, Fort Collins, CO 80523 USA
Bruce A. Draper draper@cs.colostate.edu
Department of Computer Science, Colorado State University, Fort Collins, CO 80523 USA
David A. Peterson petersod@cs.colostate.edu
Department of Computer Science, Colorado State University, Fort Collins, CO 80523 USA
Abstract
This paper investigates how behavioral
cloning can be used to decrease training time
for students learning to y on simulators.
The challenges presented to each student
must be tailored to their unique learning ex-
periences. This requires an intelligent train-
ing regime that exploits a model of each stu-
dent that predicts where the student's perfor-
mance will be de cient. Here we show that
cloning the behavior of student pilots with a
modular neural network results in the auto-
matic decomposition of the behavior into sets
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