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Proceedings Paper

Truck backer-upper: an example of self-learning in neural networks
Author(s): Derrick Nguyen; Bernard Widrow
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Paper Abstract

Neural networks can he used to solve highly nonlinear control problems. A two-layer neural network containing 26 adaptive neural elements has learned to back up a computer simulated trailer truck to a loading dock, even when initially “jackknifed. ’’ It is not yet known how to design a controller to perform this steering task. Nevertheless, the neural net was able to learn of its own accord to do this, regardless of initial conditions. Experience gained with the truck backer upper should be applicable to a wide variety of nonlinear control problems.

Paper Details

Date Published: 1 January 1990
PDF: 7 pages
Proc. SPIE 1293, Applications of Artificial Intelligence VIII, (1 January 1990); doi: 10.1117/12.21108
Show Author Affiliations
Derrick Nguyen, Stanford Univ. (United States)
Bernard Widrow, Stanford Univ. (United States)


Published in SPIE Proceedings Vol. 1293:
Applications of Artificial Intelligence VIII
Mohan M. Trivedi, Editor(s)

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