Machine Learning

Paradigms and Methods

By: Jaime G. Carbonell (Editor)

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Paperback | 23 February 1990

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Paperback
404 Pages

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18+

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22.61 x 15.24 x 2.29

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Having played a central role at the inception of artificial intelligence research, machine learning has recently reemerged as a major area of study at the very core of the subject. Solid theoretical foundations are being constructed. Machine learning methods are being integrated with powerful performance systems, and practical applications; based on established techniques are emerging.Machine Learning unifies the field by bringing together and clearly explaining the major successful paradigms for machine learning: inductive approaches, explanation-based learning, genetic algorithms, and connectionist learning methods. Each paradigm is presented in depth, providing historical perspective but focusing on current research and potential applications.The contributors are: John R. Anderson, L. B. Booker, John. H. Gennari, Jaime G. Carbonell, Oren Etzioni, Doug Fisher, Yolanda Gil, D. E. Goldberg, Gerald E. Hinton, J. H. Holland, Craig A Knoblock, Daniel. R. Kuokka, Pat Langley, David B. Leake, Steve Minton, Jack Mostow, Roger C. Schank, and Jan M. Zytkow.Jaime G. Carbonell is Professor of Computer Science at Carnegie-Mellon University.

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Non-Fiction Computing & I.T.Computer Science Artificial Intelligence

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Non-Fiction Computing & I.T.Computer Science Artificial Intelligence

Introduction: Paradigms for Machine Learning	p. 1
Model of Incremental Concept Formation	p. 11
Explanation-Based Learning: A Problem Solving Perspective	p. 63
Design by Derivational Analogy: Issues in the Automated Replay of Design Plans	p. 119
Connectionist Learning Procedures	p. 185
Classifier Systems and Genetic Algorithms	p. 235
Data-Driven Approaches to Empirical Discovery	p. 283
A Theory of the Origins of Human Knowledge	p. 313
Creativity and Learning in a Case-Based Explainer	p. 353
Author Index	p. 387
Subject Index	p. 389
Table of Contents provided by Publisher. All Rights Reserved.

Machine Learning

Paradigms and Methods

At a Glance

Paperback

Shipping

How to return your order

Defective items

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