PART ONE GENERAL ISSUES 1
Chapter 1 Understanding the Nature of Learning:Issues and Research Directions 3
CONTENTSPreface 9
Ryszard S.MichalskiChapter 2 Machine Learning:Challenges of theEighties 27
Ryszard S.Michalski,Saul Amarel,Douglas B.Lenat,Donald Michie,andPatrick H.Winston(Edited by Gail Thornburg and Ryszard Michalski)PART TWO LEARNING CONCEPTS AND RULES FROMEXAMPLES 43
Chapter 3 Learning by Augmenting Rules andAccumulating Censors 45
Patrick H.WinstonChapter 4 Learning to Predict Sequences 63
Thomas G.Dietterich and Ryszard S.MichalskiChapter 5 Shift of Bias for Inductive Concept Learning 107
Paul E. UtgoffChapter 6 The Effect of Noise on Concept Learning 149
J.Ross QUinlanChapter 7 Learning Concepts by Asking Questions 167
Claude Sammut and Ranan B.BanerjiChapter 8 Concept Learning in a Rich Input Domain:Generalization-Based Memory 193
Michael LebowitzChapter 9 Improving the Generalization Step inLearn ing 215
Yves Kodra toff and Jean-Gabriel GanasciaPART THREE COGNITIVE ASPECTS 0F LEARNING 245
Chapter 10 The Chunking of Goal Hierarchies:AGeneralized Model of Practice 247
Paul S.Rosenbloom and Allen NewellChapter 11 Knowledge Compilation:The GeneralLearning Mechanism 289
John R.AndersonChapter 12 Learning Physical Domains:Toward aTheoreticel Framework 311
Kenneth D.Forbus and Dedre GentnerPART FOUR LEARNING BY ANALOGY 349
Chapter 13 Concept Formation by IncrementalAnalogical Reasoning and Debugging 351
Mark H.BursteinChapter 14 Derivational Analogy:A Theory ofReconstructive Problem Solving andExpertise Acquisition 371
JaimeG.CarbonellPART FIVE LEARNING BY OBSERVATION ANDDISCOVERY 393
Chapter 15 Programming by Analogy 395
Nachum DershowitzChapter 16 The Search for Regularity:Four Aspects ofScientific Discovery 425
Pat Langley,Jan M.Zytkow,Herbert A.Simon,and Gary L.BradshawChapter 17 Conceptual Clustering:InventingGoal-Oriented Classifications of StructuredObjects 471
Robert E.Stepp Ⅲ and Ryszard S.MichalskiChapter 18 Program Synthesis as a Theory FormationTask:Problem Representations and SolutionMethods 499
Saul AmarelChapter 19 An Approach to Learning from Observation 571
Gerald DeJongPART SIX AN EXPLORATION OF GENERAL ASPECTS 591
OF LEARNINGChapter 20 Escaping Brittleness:The Possibilities ofGeneral-Purpose Learning AlgorithmsApplied to Parallel Rule-Based Systems 593
John H.HollandChapter 21 Learning from Positive-Only Examples:TheSubset Principle and Three Case Studies 625
Robert C.BerwickChapter 22 Precondition Analysis:Learning ControlInformation 647
Bernard SilverBibliography of Recent Machine Learning Research 671
Smadar T.Kedar-Cabelli and Sridhar MahadevanUpdated Glossary of Selected Terms In Machine Learning 707
About the Authors 715
Author Index 725
Subject Index 729