Title:
The Learning of Reactive Control Parameters Through Genetic Algorithms
The Learning of Reactive Control Parameters Through Genetic Algorithms
| dc.contributor.author | Arkin, Ronald C. | |
| dc.contributor.author | Pearce, Michael | |
| dc.contributor.author | Ram, Ashwin | |
| dc.contributor.corporatename | Georgia Institute of Technology. College of Computing | |
| dc.date.accessioned | 2008-06-09T19:54:01Z | |
| dc.date.available | 2008-06-09T19:54:01Z | |
| dc.date.issued | 1992 | |
| dc.description.abstract | This paper explores the application of genetic algorithms to the learning of local robot navigation behaviors for reactive control systems. Our approach is to train a reactive control system in various types of environments, thus creating a set of "ecological niches" that can be used in similar environments. The use of genetic algorithms as an unsupervised learning method for a reactive control architecture greatly reduces the effort required to configure a navigation system. Findings from computer simulations of robot navigation through various types of environments are presented. | en_US |
| dc.identifier.uri | http://hdl.handle.net/1853/22447 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.subject | Genetic algorithms | en_US |
| dc.subject | Reactive control | en_US |
| dc.subject | Robot behavior | en_US |
| dc.subject | Robot navigation | en_US |
| dc.title | The Learning of Reactive Control Parameters Through Genetic Algorithms | en_US |
| dc.type | Text | |
| dc.type.genre | Paper | |
| dspace.entity.type | Publication | |
| local.contributor.author | Arkin, Ronald C. | |
| local.contributor.corporatename | College of Computing | |
| local.contributor.corporatename | Mobile Robot Laboratory | |
| local.contributor.corporatename | Institute for Robotics and Intelligent Machines (IRIM) | |
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