The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The truck backer-upper: an example of self-learning in neural networks
Abstract
Neural networks can be 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.>
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WIDROW, B., & HOFF, M. E. (1960) · doi:10.21236/ad0241531 · Cited by 4,009
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Forward models: supervised learning with a distal teacher
Jordan, M. I., & Rumelhart, D. E. (1992) · Cognitive Science · doi:10.1207/s15516709cog1603_1 · Cited by 1,451
Nguyen, D., & Widrow, B. (1990) · 1990 IJCNN International Joint Conference on Neural Networks · doi:10.1109/ijcnn.1990.137819 · Cited by 1,375
Metadata
- Authors
- Nguyen, & Widrow
- Venue
- International Joint Conference on Neural Networks
- Publisher
- IEEE
- Published
- 1989
- Pages
- 357-363 vol.2
- OpenAlex
- W3148194443
- Cited by
- 449
- References
- 1
- FWCI
- 17.52
- Type
- conference paper
- Language
- en
- Open access
- closed
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