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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.

@inproceedings{ksmith06learningEELC,
  author={Kenny Smith and Andrew D. M. Smith and Richard A. Blythe and Paul Vogt},
  title={Cross-situational learning: a mathematical approach},
  year={2006},
  pages={31-44},
  editor={P. Vogt and Y. Sugita and E. Tuci and C. Nehaniv},
  publisher={Springer Berlin/Heidelberg},
  booktitle={Symbol Grounding and Beyond: Proceedings of the Third International Workshop on the Emergence and Evolution of Linguistic Communication},
  doi={10.1007/11880172_3},
  url={http://www.isrl.uiuc.edu/~amag/langev/paper/ksmith06learningEELC.html}
}

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