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Neural Networks in Adaptive Training


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Current project members

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Funding

This work has been funded by a CASI grant:

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Research Summary and Publications

SymSystems is developing pilot training systems for NASA. Based on their experience, student pilots not only learn at different rates, but in different manners. Some students, for example, tend to overcompensate early in their training while others experience problems with take-off and landing. The challenges presented to each student must be tailored to their unique learning experiences. This requires an intelligent training regime that exploits a model of each student that predicts where the student's performance will be deficient. This project developed artificial neural network algorithms for predicting student actions. Results show that modular neural networks can discover when a student acquires the various skills necessary to fly the simulated aircraft. This provides a basis for future intelligent training systems.

Publications on this project include the following:

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Neural Networks in Adaptive Training Research in CS at CSU, Charles W. Anderson / anderson@cs.colostate.edu

Copyright © 1998 Charles Anderson