Machine Learning: A Guide to Current Research

412 Pages·1986·13.404 MB·English

by  Tom M. Mitchell, Jaime G. Carbonell, Ryszard S. Michalski (auth.)

MACHINE LEARNING: A Guide to Current Research
THE KLUWER INTERNATIONAL SERIES
IN ENGINEERING AND COMPUTER SCIENCE
KNOWLEDGE REPRESENTATION, LEARNING
AND EXPERT SYSTEMS
Consulting Editor
Tom M. Mitchell
MACHINE LEARNING
A Guide to Current Research
edited by
Tom M. Mitchell
Rutgers University
Jaime G. Carbonell
Carnegie-Mellon University
Ryszard S. Michalski
University of Illinois
KLUWER ACADEMIC PUBLISHERS
Boston/DordrechtiLancaster
Distributors for North America:
Kluwer Academic Publishers
101 Philip Drive
Assinippi Park
Norwell, Massachusetts 02066, USA
Distributors for tbe UK and Ireland:
K1uwer Academic Publishers
MTP Press Limited
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Lancaster LAI lRN, UNITED KINGDOM
Distributors for all otber countries:
K1uwer Academic Publishers Group
Distribution Centre
Post Office Box 322
3300 AH Dordrecht, THE NETHERLANDS
Library of Congress Catalo~ng-in-Publication Data:
Machine learning.
(The Kluwer international series in engineering and
computer science ; SECS 12)
Bibliography: p.
Includes index.
I. Machine learning-Addresses, essays, lectures.
2. Artificial intelligence-Addresses, essays, lectures.
I. Mitchell, Tom M. (Tom Michael), 1951-
II. Carbonell, Jaime G. (Jaime Guillermo)
III. Michalski, Ryszard Stanislaw, 1937-
IV. Series.
Q325.M318 1986 006.3'2 86-2766
ISBN-I3: 978-1-4612-9406-1 e-ISBN-I3: 978-1-4613-2279-5
DOl: 10.1007/978-1-4613-2279-5
Copyrlgbt © 1986 by K1uwer Academic Publishers
Softcover reprint of the hardcover 1st edition 1986
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or trans
mitted in any form or by any means, mechanical, photocopying, recording, or otherwise, without written
permission of the publisher, Kluwer Academic Publishers, 101 Philip Drive, Assinippi Park, Norwell, MA
02061.
Third printing 1988
Table of Contents
CONTRIBUTING AUTHORS xi
xiii
PREFACE
JUDGE: A CASE-BASED REASONING SYSTEM 1
William M. Bain
CHANGING LANGUAGE WHILE LEARNING RECURSIVE 5
DESCRIPTIONS FROM EXAMPLES
Ranan B. Banerji
LEARNING BY DISJUNCTIVE SPANNING 11
Gary L. Bradshaw
TRANSFER OF KNOWLEDGE BETWEEN TEACHING AND 15
LEARNING SYSTEMS
P. Brazdil
SOME APPROACHES TO KNOWLEDGE ACQUISITION 19
Bruce G. Buchanan
ANALOGICAL LEARNING WITH MULTIPLE MODELS 25
Mark H. Burstein
THE WORLD MODELERS PROJECT: OBJECTIVES AND 29
SIMULATOR ARCHITECTURE
Jaime Carbonell and Greg Hood
THE ACQUISITION OF PROCEDURAL KNOWLEDGE THROUGH 35
INDUCTIVE LEARNING
Kaihu Chen
LEARNING STATIC EVALUATION FUNCTIONS BY LINEAR 39
REGRESSION
Jens Christensen
PLAN INVENTION AND PLAN TRANSFORMATION 43
Gregg C. Collins
A BRIEF OVERVIEW OF EXPLANATORY SCHEMA 47
ACQUISITION
Gerald Dejong
THE EG PROJECT: RECENT PROGRESS 51
Thomas G. Dietterich
vi
LEARNING CAUSAL RELATIONS 55
Richard J. Doyle
FUNCTIONAL PROPERTIES AND CONCEPT FORMATION 59
J. Daniel Easterlin
EXPLANATION-BASED LEARNING IN LOGIC CIRCUIT DESIGN 63
Thomas Ellman
A PROPOSED METHOD OF CONCEPTUAL CLUSTERING FOR 67
STRUCTURED AND DECOMPOSABLE OBJECTS
Douglas Fisher
EXPLOITING FUNCTIONAL VOCABULARIES TO LEARN 71
STRUCTURAL DESCRIPTIONS
Nicholas S. Flann and Thomas G. Dietterich
COMBINING NUMERIC AND SYMBOLIC LEARNING 75
TECHNIQUES
Richard H. Granger. Jr. and Jeffrey C. Schlimmer
LEARNING BY UNDERSTANDING ANALOGIES 81
Russell Greiner
ANALOGICAL REASONING IN THE CONTEXT OF ACQUIRING 85
PROBLEM SOLVING EXPERTISE
Rogers Hall
PLANNING AND LEARNING IN A DESIGN DOMAIN: THE 89
PROBLEMS PLAN INTERACTIONS
Kristian J. Hammond
INFERENCE OF INCORRECT OPERATORS 93
Haym Hirsh and Derek Sleeman
A CONCEPTUAL FRAMEWORK FOR CONCEPT 99
IDENTIFICATION
Robert C. Holte
NEURAL MODELING AS ONE APPROACH TO MACHINE 103
LEARNING
Greg Hood
STEPS TOWARD BUILDING A DYNAMIC MEMORY 109
Larry Hunter
vii
LEARNING BY COMPOSITION 115
Glenn A. Iba
KNOWLEDGE ACQUISITION: INVESTIGATIONS AND GENERAL 119
PRINCIPLES
Gary S. Kahn
PURPOSE-DIRECTED ANALOGY: A SUMMARY OF CURRENT 123
RESEARCH
Smadar Kedar-Cabelli
DEVELOPMENT OF A FRAMEWORK FOR CONTEXTUAL 127
CONCEPT LEARNING
Richard M. Keller
ON SAFELY IGNORING HYPOTHESES 133
Kevin T. Kelly
A MODEL OF ACQUIRING PROBLEM SOLVING EXPERTISE 137
Dennis Kibler and Rogers P. Hall
ANOTHER LEARNING PROBLEM: SYMBOLIC PROCESS 141
PREDICTION
Heedong Ko
LEARNING AT LRI ORSAY 145
Yves Kodratoff
COPER: A METHODOLOGY FOR LEARNING INVARIANT 151
FUNCTIONAL DESCRIPTIONS
Mieczyslaw M. Kokar
USING EXPERIENCE AS A GUIDE FOR PROBLEM SOLVING 155
Janet L. Kolodner and Robert L. Simpson
HEURISTICS AS INVARIANTS AND ITS APPLICATION TO 161
LEARNING
Richard E. Korf
COMPONENTS OF LEARNING IN A REACTIVE ENVIRONMENT 167
Pat Langley, Dennis Kibler. and Richard Granger
THE DEVELOPMENT OF STRUCTURES THROUGH 173
INTERACTION
Robert W. Lawler
viii
COMPLEX LEARNING ENVIRONMENTS: HIERARCHIES AND 179
THE USE OF EXPLANATION
Michael Lebowitz
PREDICTION AND CONTROL IN AN ACTIVE ENVIRONMENT 183
Alan J. MacDonald
BETTER INFORMATION RETRIEVAL THROUGH LINGUISTIC 189
SOPHISTICATION
Michael L. Mauldin
MACHINE LEARNING RESEARCH IN THE ARTIFICIAL 193
INTELLIGENCE LABORATORY AT ILLINOIS
Ryszard S. Michalski
OVERVIEW OF THE PRODIGY LEARNING APPRENTICE 199
Steven Minton
A LEARNING APPRENTICE SYSTEM FOR VLSI DESIGN 203
Tom M. Mitchell. Sridhar Mahadevan, and Louis I. Steinberg
GENERALIZING EXPLANATIONS OF NARRATIVES INTO 207
SCHEMATA
Raymond J. Mooney
WHY ARE DESIGN DERIVATIONS HARD TO REPLAY? 213
Jack Mostow
AN ARCHITECTURE FOR EXPERIENTIAL LEARNING 219
Michael C. Mozer, Klaus P. Gross
KNOWLEDGE EXTRACTION THROUGH LEARNING FROM 227
EXAMPLES
Igor Mozetic
LEARNING CONCEPTS WITH A PROTOTYPE-BASED MODEL 233
FOR CONCEPT REPRESENTATION
Donna J. Nagel
RECENT PROGRESS ON THE MATHEMATICIAN'S 237
APPRENTICE PROJECT
Paul O'Rorke
ACQUIRING DOMAIN KNOWLEDGE FROM FRAGMENTS OF 241
ADVICE
Bruce W. Porter, Ray Bareiss, and Adam Farquhar
ix
CALM: CONTESTATION FOR ARGUMENTATIVE LEARNING 247
MACHINE
J. Quinqueton and J. Sallantin
DIRECTED EXPERIMENTATION FOR THEORY REVISION AND 255
CONCEPTUAL KNOWLEDGE ACQUISITION
Shankar A. Rajamoney
GOAL-FREE LEARNING BY ANALOGY 261
Alain Rappaport
A SCIENTIFIC APPROACH TO PRACTICAL INDUCTION 269
Larry Rendell
EXPLORING SHIFTS OF REPRESENTATION 275
Patricia J. Riddle
CURRENT RESEARCH ON LEARNING IN SOAR 281
Paul S. Rosenbloom. John E. Laird. Allen Newell. Andrew Golding.
and Amy Unruh
LEARNING CONCEPTS IN A COMPLEX ROBOT WORLD 291
Claude Sammut and David Hume
LEARNING EVALUATION FUNCTIONS 295
Patricia A. Schooley
LEARNING FROM DATA WITH ERRORS 299
Jakub Segen
EXPLANATION-BASED MANIPULATOR LEARNING 303
Alberto Maria Segre
LEARNING CLASSICAL PHYSICS 307
Jude W. Shavlik
VIEWS AND CAUSALITY IN DISCOVERY: MODELLING 311
HUMAN INDUCTION
Jeff Shrager
LEARNING CONTROL INFORMATION 317
Bernard Silver
AN INVESTIGATION OF THE NATURE OF MATHEMATICAL 321
DISCOVERY
Michael H. Sims
x
LEARNING HOW TO REACH A GOAL: A STRATEGY FOR 327
THE MULTIPLE CLASSES CLASSIFICATION PROBLEM
Henri Soldano and Helene Pigot
CONCEPTUAL CLUSTERING OF STRUCTURED OBJECTS 333
R. E. Stepp
LEARNING IN INTRACTABLE DOMAINS 337
Prasad V. T adepalli
ON COMPILING EXPLAINABLE MODELS OF A DESIGN 343
DOMAIN
Christopher Tong
WHAT CAN BE LEARN ED? 349
L.G. Valiant
LEARNING HEURISTIC RULES FROM DEEP REASONING 353
Walter Van De Velde
LEARNING A DOMAIN THEORY BY COMPLETING 359
EXPLANATIONS
Kurt VanLehn
LEARNING IMPLEMENTATION RULES WITH OPERATING- 363
CONDITIONS DEPENDING ON INTERNAL STRUCTURES
IN VLSI DESIGN
Masanobu Watanabe
OVERVIEW OF THE ODYSSEUS LEARNING APPRENTICE 369
David C. Wilkins. William J. Clancey. and Bruce G. Buchanan
LEARNING FROM EXCEPTIONS IN DATABASES 375
Keith E. Williamson
LEARNING APPRENTICE SYSTEMS RESEARCH AT 379
SCHLUMBERGER
Howard Winston. Reid Smith. Michael Kleyn. Tom Mitchell. and
Bruce Buchanan
LANGUAGE ACQUISITION: LEARNING PHRASES IN CONTEXT 385
Uri Zernik and Michael Dyer
REFERENCES 391
INDEX 425