A simplified neural network solution through problem decomposition: the case of the truck backer-upper
D.H. Nguyen and B. Widrow (1990) demonstrated that a feedforward neural network can be trained to steer a tractor-trailer truck to a dock while backing up. The feedforward network they used to control the truck contained 25 hidden units and required extensive training. The authors demonstrate that a...
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Veröffentlicht in: | IEEE transactions on neural networks 1993-07, Vol.4 (4), p.718-720 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | D.H. Nguyen and B. Widrow (1990) demonstrated that a feedforward neural network can be trained to steer a tractor-trailer truck to a dock while backing up. The feedforward network they used to control the truck contained 25 hidden units and required extensive training. The authors demonstrate that a very simple solution to the truck backer-upper exists and can be found by decomposing the problem into subtasks. By hard-wiring these control laws into a network, they found a controller with only two hidden units that performs as well as the larger controller trained from scratch. This approach could be used to build up more complex controllers from simple components.< > |
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ISSN: | 1045-9227 1941-0093 |
DOI: | 10.1109/72.238326 |