The Springer International Series in Engineering and Computer Science

Foundations of Knowledge Acquisition

Machine Learning

Editors: Meyrowitz, Alan L., Chipman, Susan (Eds.)

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About this book

One of the most intriguing questions about the new computer technology that has appeared over the past few decades is whether we humans will ever be able to make computers learn. As is painfully obvious to even the most casual computer user, most current computers do not. Yet if we could devise learning techniques that enable computers to routinely improve their performance through experience, the impact would be enormous. The result would be an explosion of new computer applications that would suddenly become economically feasible (e. g. , personalized computer assistants that automatically tune themselves to the needs of individual users), and a dramatic improvement in the quality of current computer applications (e. g. , imagine an airline scheduling program that improves its scheduling method based on analyzing past delays). And while the potential economic impact of successful learning methods is sufficient reason to invest in research into machine learning, there is a second significant reason: studying machine learning helps us understand our own human learning abilities and disabilities, leading to the possibility of improved methods in education. While many open questions remain about the methods by which machines and humans might learn, significant progress has been made.

Table of contents (10 chapters)

  • Learning = Inferencing + Memorizing

    Michalski, Ryszard S.

    Pages 1-41

  • Adaptive Inference

    Segre, Alberto (et al.)

    Pages 43-81

  • On Integrating Machine Learning with Planning

    DeJong, Gerald F. (et al.)

    Pages 83-116

  • The Role of Self-Models in Learning to Plan

    Collins, Gregg (et al.)

    Pages 117-143

  • Learning Flexible Concepts Using a Two-Tiered Representation

    Michalski, R. S. (et al.)

    Pages 145-202

Buy this book

eBook $109.00
price for USA in USD (gross)
  • ISBN 978-0-585-27366-2
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $179.99
price for USA in USD
  • ISBN 978-0-7923-9278-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $149.99
price for USA in USD
  • ISBN 978-1-4757-8392-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Foundations of Knowledge Acquisition
Book Subtitle
Machine Learning
Editors
  • Alan L. Meyrowitz
  • Susan Chipman
Series Title
The Springer International Series in Engineering and Computer Science
Series Volume
195
Copyright
1993
Publisher
Springer US
Copyright Holder
Springer Science+Business Media New York
eBook ISBN
978-0-585-27366-2
DOI
10.1007/b102257
Hardcover ISBN
978-0-7923-9278-1
Softcover ISBN
978-1-4757-8392-6
Series ISSN
0893-3405
Edition Number
1
Number of Pages
XII, 334
Topics