Foundations of Knowledge Acquisition

Foundations of Knowledge Acquisition : Cognitive Models of Complex Learning

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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 ofsuccessful 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 aboutthe methods by which machines and humans might learn, significant progress has been made.
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Product details

  • Hardback | 339 pages
  • 155 x 235 x 20.57mm | 1,490g
  • Dordrecht, Netherlands
  • English
  • 1993 ed.
  • XI, 339 p.
  • 0792392779
  • 9780792392774

Table of contents

Foreword. Preface. 1. Acquisition of LISP Programming Skill; J.R. Anderson, A.T. Corbett. 2. Learning by Explaining Examples to Oneself: A Computational Model; K. VanLehn, R.M. Jones. 3. Learning Schemas from Explanations in Practical Electronics; D.E. Kieras. 4. Statistical and Cognitive Models of Learning Through Instruction; S.P. Marshall. 5. The Interaction Between Konwledge and Practice in the Acquisition of Cognitive Skills; S. Ohlsson. 6. Correcting Imperfect Domain Theories: A Knowledge-Level Analysis; S.B. Huffman, D.J. Pearson, J.E. Laird. 7. A Cognitive Science Approach to Case-Based Planning; K.J.Hammond, C.M. Seifert. 8. Bias in Planning and Explanation-Based Learning; P.S. Rosenbloom, Soowon Lee, A. Unruh. 9. Knowledge Acquisition and Natural Language Processing; R. Wilensky. Index.
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