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Artificial Intelligence -

Artificial Intelligence (eBook)

Margaret A. Boden (Herausgeber)

eBook Download: PDF
1996 | 1. Auflage
376 Seiten
Elsevier Science (Verlag)
978-0-08-052759-8 (ISBN)
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Artificial Intelligence is the study of how to build or program computers to enable them to do what minds can do. This volume discusses the ways in which computational ideas and computer modeling can aid our understanding of human and animal minds. Major theoretical approaches are outlined, as well as some promising recent developments. Fundamental philosophical questions are discussed along with topics such as: the differences between symbolic and connectionist AI, planning and problem solving, knowledge representation, learning, expert systems, vision, natural language, creativity, and human-computer interaction. This volume is suitable for any psychologist, philosopher, or computer scientist wanting to know the current state of the art in this area of cognitive science.

Key Features
* Up-to-date account of how computational ideas and techniques are relevant to psychology
* Includes discussions of classical (symbolic) AI, of connectionism (neural nets), of evolutionary programming, and of A-Life
* Discusses a wide range of psychology from low-level vision to creativity
Artificial Intelligence is the study of how to build or program computers to enable them to do what minds can do. This volume discusses the ways in which computational ideas and computer modeling can aid our understanding of human and animal minds. Major theoretical approaches are outlined, as well as some promising recent developments. Fundamental philosophical questions are discussed along with topics such as: the differences between symbolic and connectionist AI, planning and problem solving, knowledge representation, learning, expert systems, vision, natural language, creativity, and human-computer interaction. This volume is suitable for any psychologist, philosopher, or computer scientist wanting to know the current state of the art in this area of cognitive science. - Up-to-date account of how computational ideas and techniques are relevant to psychology- Includes discussions of "e;classical"e; (symbolic) AI, of connectionism (neural nets), of evolutionary programming, and of A-Life- Discusses a wide range of psychology from low-level vision to creativity

Cover 1
Contents 6
Contributors 12
Foreword 14
Preface 16
Chapter 1. Philosophical Foundations 20
I. An Evolving Engagement 20
II. Symbol-System AI 22
III. Connectionism 26
IV. Artificial Life 33
V. The Wasteland 38
References 39
Chapter 2. Planning and Problem Solving 42
I. Some Basic Ideas 43
II. The General Problem Solver 47
III. STRIPS 52
IV. Handling Interference 55
V. Nonlinear Planning 57
VI. More Sophisticated Planning 62
VII. Planning and Cognitive Science 67
References 72
Chapter 3. Representation of Knowledge 74
I. Representation and Knowledge 74
II. Classical Approaches 87
References 104
Chapter 4. Machine Learning 108
I. Introduction 108
II. Knowledge-Free Inductive Learning Systems 112
III. Learning in Situated Agents 129
IV. Theoretical Models of Learning 137
V. Learning from Single Examples 142
VI. Forming New Concepts 146
VII. Summary 148
References 149
Chapter 5. Connectionism and Neural Networks 154
I. Introduction 154
II. Understanding and Modeling Cognition and Perception 154
III. Reference Sources 156
IV. Biological Origins 156
V. Early Developments: Logical Models 159
VI. Adaptive Networks 160
VII. The Dartmouth Conference 160
VIII. Perceptrons 161
IX. Adalines and the LMS Algorithm 164
X. Minsky and Papert’s Perceptrons 164
XI. Back Propagation 165
XII. NETtalk 169
XIII. The Future 171
References 173
Chapter 6. Expert Systems and Theories of Knowledge 176
I. Introduction 176
II. Knowledge Engineering-The First Decade 177
III. Second-Generation Expert Systems„From Decision Making to Expertise 184
IV. The Third Decade„Systematic Engineering of Knowledge 192
V. Conclusions 199
References 199
Chapter 7. Machine Vision 202
I. Introduction 202
II. Image Formation 206
III. Feature Detection 210
IV. Building Descriptions Using General Properties of Objects 214
V. Using Object Models 229
VI. Conclusion 243
References 244
Chapter 8. Natural Language Processing 248
I. Introduction 248
II. Computational Theories of Processing 251
III. Conclusion 281
IV. Further Reading 282
References 283
Chapter 9. Creativity 286
I. The Definition of Creativity 286
II. Impossibilist Creativity 288
III. Improbabilist Creativity 291
IV. AI Models of the Arts 296
V. AI Models of Science 301
VI. Self-Transforming Programs 304
VII. Conclusion 308
References 308
Chapter 10. Human–Computer Interaction 312
I. Interacting with Computers 312
II. The Psychology of Computer Use 320
III. Modeling Human-Computer Interaction 326
IV. System Development 330
V. Evaluation 334
VI. Beyond Human–Computer Interaction 337
References 341
Chapter 11. Artificial Life and the Animat Approach to Artificial Intelligence 344
I. What Is Artificial Life? 344
II. The Animat Approach to AI 345
III. What Is Adaptive Behavior? 348
IV. Preprogrammed Behaviors 349
V. Learned Behaviors 353
VI. Evolved Behaviors 361
VII. Conclusion 369
References 370
Index 374

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