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Cross-Situational Learning: A Mathematical Approach

  • Kenny Smith
  • Andrew D. M. Smith
  • Richard A. Blythe
  • Paul Vogt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4211)

Abstract

We present a mathematical model of cross-situational learning, in which we quantify the learnability of words and vocabularies. We find that high levels of uncertainty are not an impediment to learning single words or whole vocabulary systems, as long as the level of uncertainty is somewhat lower than the total number of meanings in the system. We further note that even large vocabularies are learnable through cross-situational learning.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Kenny Smith
    • 1
  • Andrew D. M. Smith
    • 1
  • Richard A. Blythe
    • 2
  • Paul Vogt
    • 1
    • 3
  1. 1.Language Evolution and Computation Research UnitUniversity of Edinburgh 
  2. 2.School of PhysicsUniversity of Edinburgh 
  3. 3.ILK/Language and Information ScienceTilburg UniversityThe Netherlands

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