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Conceptual Knowledge Acquisition in Search

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Computational Models of Learning

Part of the book series: Symbolic Computation ((1064))

Abstract

This paper concerns effective and efficient concept learning in difficult situations, when the data are uncertain and learning must be incremental. The probabilistic learning system PLS is outlined, and some ideas and principles underlying it are developed. PLS1 was the first AI system to use probabilistic conceptual clustering, and to exhibit optimal learning. A new system PLSO may permit tractable induction of structure and relations using “second order” clustering.

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Authors and Affiliations

  1. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, 61801, USA

    Larry Rendell

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  1. Larry Rendell
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  1. Institute of Informatics, Warsaw University, PKiN, pok. 850, PL-00-901, Warszawa, Poland

    Leonard Bolc

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Rendell, L. (1987). Conceptual Knowledge Acquisition in Search. In: Bolc, L. (eds) Computational Models of Learning. Symbolic Computation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-82742-6_4

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  • DOI: https://doi.org/10.1007/978-3-642-82742-6_4

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