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Computational Models of Learning

  • Book
  • © 1987

Overview

Part of the book series: Symbolic Computation (SYMBOLIC)

Part of the book sub series: Artificial Intelligence (1064)

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Table of contents (5 chapters)

Keywords

About this book

In recent years, machine learning has emerged as a significant area of research in artificial intelligence and cognitive science. At present, research in the field is being intensified from both the point of view of theory and of implementation, and the results are being introduced in practice. Machine learning has recently become the subject of interest of many young and talented scientists whose bold ideas have greatly contributed to the broadening of knowledge in this rapidly developing field of science. This situation has manifested itself in an increasing number of valuable contributions to scientific journals. However, such papers are necessarily compact descriptions of research problems. Computational Models of Learning supplements these contributions and is a collection of more extensive essays. These essays provide the reader with an increased knowledge of carefully selected problems of machine learning.

Editors and Affiliations

  • Institute of Informatics, Warsaw University, Warszawa, Poland

    Leonard Bolc

Bibliographic Information

  • Book Title: Computational Models of Learning

  • Editors: Leonard Bolc

  • Series Title: Symbolic Computation

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

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 1987

  • Softcover ISBN: 978-3-642-82744-0Published: 15 December 2011

  • eBook ISBN: 978-3-642-82742-6Published: 06 December 2012

  • Edition Number: 1

  • Number of Pages: IX, 208

  • Topics: Artificial Intelligence

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