Hybrid distributed/local connectionist architectures

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Summary form only given, as follows. A class of neural-network architectures is described that uses both distributed and local representation. The distributed representations are used for input and output, thereby enabling associative, noise-tolerant interaction with the environment. Internally, all representations are fully local. This simplifies weight assignment and makes the networks easy to configure for specific applications. These hybrid distributed/local architectures are especially useful for applications were structured information needs to be represented. Three such applications are briefly discussed: a scheme for knowledge representation, a connectionist rule-based system, and a knowledge-base browser.

Original languageEnglish (US)
Title of host publicationIJCNN Int Jt Conf Neural Network
Editors Anon
PublisherPubl by IEEE
Number of pages1
StatePublished - Dec 1 1989
EventIJCNN International Joint Conference on Neural Networks - Washington, DC, USA
Duration: Jun 18 1989Jun 22 1989


OtherIJCNN International Joint Conference on Neural Networks
CityWashington, DC, USA


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