机器学习 第2卷 上下PDF电子书下载

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