articlePsychological ReviewJan 1, 2004Closed access

SUSTAIN: A Network Model of Category Learning.

The University of Texas at Austin

PubMed
Indexed incrossrefpubmed

Abstract

SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told that a bat is a mammal instead of a bird), SUSTAIN recruits an additional cluster to represent the surprising event. Newly recruited clusters are available to explain future events and can themselves evolve into prototypes-attractors-rules. SUSTAIN's discovery of category substructure is affected not only by the structure of the world but by the nature of the learning task and the learner's goals. SUSTAIN successfully…

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Authors

3

Topics & keywords

Keywords
  • Unsupervised learning
  • Artificial intelligence
  • Inference
  • Event (particle physics)
  • Concept learning
  • Identification (biology)
  • Machine learning
  • Social learning
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