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  • T. Samad
  • 1988
A connectionist architecture, called RUBICON, for implementing rule-based systems, is described. RUBICON uses both distributed and local representations. Input and output are fully distributed, allowing the use of microfeatures for robust interfacing to the external world. All input units, however, are local. The local internal representation results in(More)
  • T. Samad
  • 1989
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(More)
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