A Simplified Neural-Network Solution Through Problem Decomposition: The Case of the Truck Backer-Upper

Abstract

September 01 1992 A Simplified Neural-Network Solution through Problem Decomposition: The Case of the Truck Backer-Upper In Special Collection: CogNet Robert E. Jenkins, Robert E. Jenkins The Applied Physics Laboratory, The Johns Hopkins University, Baltimore, MD 21218 USA Search for other works by this author on: This Site Google Scholar Ben P. Yuhas Ben P. Yuhas The Applied Physics Laboratory, The Johns Hopkins University, Baltimore, MD 21218 USA Search for other works by this author on: This Site Google Scholar Author and Article Information Robert E. Jenkins The Applied Physics Laboratory, The Johns Hopkins University, Baltimore, MD 21218 USA Ben P. Yuhas The Applied Physics Laboratory, The Johns Hopkins University, Baltimore, MD 21218 USA *Current address: Bellcore MRE 2E-330, Morristown, NJ 07962-1910 USA. Received: December 17 1991 Accepted: March 04 1992 Online ISSN: 1530-888X Print ISSN: 0899-7667 © 1992 Massachusetts Institute of Technology1992 Neural Computation (1992) 4 (5): 647–649. https://doi.org/10.1162/neco.1992.4.5.647 Article history Received: December 17 1991 Accepted: March 04 1992 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn MailTo Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Robert E. Jenkins, Ben P. Yuhas; A Simplified Neural-Network Solution through Problem Decomposition: The Case of the Truck Backer-Upper. Neural Comput 1992; 4 (5): 647–649. doi: https://doi.org/10.1162/neco.1992.4.5.647 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsNeural Computation Search Advanced Search This content is only available as a PDF. © 1992 Massachusetts Institute of Technology1992 Article PDF first page preview Close Modal You do not currently have access to this content.