Foundations of Knowledge Acquisition: Machine Learning

Author:   Alan L. Meyrowitz ,  Susan Chipman
Publisher:   Springer
Edition:   1993 ed.
Volume:   195
ISBN:  

9780792392781


Pages:   334
Publication Date:   31 January 1993
Format:   Hardback
Availability:   In Print   Availability explained
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Foundations of Knowledge Acquisition: Machine Learning


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Overview

The two volumes of ""Foundations of Knowledge Acquisition"" document the recent progress of basic research in knowledge acquisition sponsored by the Office of Naval Research. In this volume, significant progress in machine learning is reported along a variety of fronts. Chapters include work in analogical reasoning; induction and discovery; learning and planning; learning by competition, using genetic algorithms; and theoretical limitations. Knowledge acquisition as pursued under the ARI was a coordinated research thrust into both machine learning and human learning. Chapters in the accompanying volume ""Cognitive Models of Complex Learning"" include summaries of work by cognitive scientists who do computational modelling of human learning. In fact, an accomplishment of research previously sponsored by ONR's Cognitive Science Program was insight into the knowledge and skills that distinguish human novices from human experts in various domains; the cognitive interest in the ARI was then to characterize how the transition from novice to expert actually takes place.

Full Product Details

Author:   Alan L. Meyrowitz ,  Susan Chipman
Publisher:   Springer
Imprint:   Springer
Edition:   1993 ed.
Volume:   195
Dimensions:   Width: 15.50cm , Height: 2.00cm , Length: 23.50cm
Weight:   1.480kg
ISBN:  

9780792392781


ISBN 10:   0792392787
Pages:   334
Publication Date:   31 January 1993
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Learning = Inferencing + Memorizing.- Adaptive Inference.- On Integrating Machine Learning with Planning.- The Role of Self-Models in Learning to Plan.- Learning Flexible Concepts Using a Two-Tiered Representation.- Competition-Based Learning.- Problem Solving via Analogical Retrieval and Analogical Search Control.- A View of Computational Learning Theory.- The Probably Approximately Correct (PAC) and Other Learning Models.- On the Automated Discovery of Scientific Theories.

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