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Scandinavian Workshop on Algorithm Theory

SWAT 1992: Algorithm Theory — SWAT '92 pp 19–29Cite as

Memory limited inductive inference machines

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 621))

Abstract

The traditional model of learning in the limit is restricted so as to allow the learning machines only a fixed, finite amount of memory to store input and other data. A class of recursive functions is presented that cannot be learned deterministically by any such machine, but can be learned by a memory limited probabilistic leaning machine with probability 1.

Supported in part by NSF Grant CCR-9020079.

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Author information

Authors and Affiliations

  1. Institute of Mathematics and Computer Science, University of Latvia, Raina bulvāris 29, 226250, Riga, Latvia

    Rūsinš Freivalds

  2. Department of Computer Science and Institute for Advanced Computer Studies, The University of Maryland, 20742, College Park, MD, USA

    Carl H. Smith

Authors
  1. Rūsinš Freivalds
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  2. Carl H. Smith
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Editor information

Otto Nurmi Esko Ukkonen

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© 1992 Springer-Verlag Berlin Heidelberg

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Freivalds, R., Smith, C.H. (1992). Memory limited inductive inference machines. In: Nurmi, O., Ukkonen, E. (eds) Algorithm Theory — SWAT '92. SWAT 1992. Lecture Notes in Computer Science, vol 621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55706-7_2

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  • DOI: https://doi.org/10.1007/3-540-55706-7_2

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-55706-7

  • Online ISBN: 978-3-540-47275-9

  • eBook Packages: Springer Book Archive

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