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- Publisher
- Springer Journals
- Copyright
- Copyright
- Subject
- Computer Science; Artificial Intelligence; Computer Science, general
- ISSN
- 0269-2821
- eISSN
- 1573-7462
- DOI
- 10.1007/BF00140398
- Publisher site
- See Article on Publisher Site
Abstract
At a symbolic level cognition can be modelled as a production system where meaning units are represented as condition-action rules. Anderson (1982, 1987) provides a good example of how learning can occur with this type of knowledge representation. At a subsymbolic level cognition can be modelled with a connectionist network where meaning units are represented as patterns of parallel distributed activity. The work of the McClelland and Rumelhart (1986) group is a prototype of this approach. We elaborate on these two approaches to learning and contrast the symbolic search space paradigm with the connectionist paradigm.
Journal
Artificial Intelligence Review – Springer Journals
Published: Jun 9, 2004