Machine Learning: A Guide to Current Research PDF
Preview Machine Learning: A Guide to Current Research
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 Falcon House, Queen Square 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
The list of books you might like
