Rent 9780521116398 | The Quest for Artificial Intelligence

Summary Table of Contents Author Biography

This book is the definitive history of the field of artificial intelligence (AI), tracing its history from the dreams of early pioneers to the more successful work of today's AI engineers. The book includes many diagrams and easy-to-understand descriptions of AI programs that will help the casual reader gain an understanding of how these and other AI systems actually work.

Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This bo... MORE

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Preface	p. xiii
Beginnings	p. 1
Dreams and Dreamers	p. 3
Clues	p. 10
From Philosophy and Logic	p. 10
From Life Itself	p. 15
From Engineering	p. 25
Early Explorations: 1950s and 1960s	p. 47
Gatherings	p. 49
Session on Learning Machines	p. 49
The Dartmouth Summer Project	p. 52
Mechanization of Thought Processes	p. 56
Pattern Recognition	p. 62
Character Recognition	p. 62
Neural Networks	p. 64
Statistical Methods	p. 73
Applications of Pattern Recognition to Aerial Reconnaissance	p. 74
Early Heuristic Programs	p. 81
The Logic Theorist and Heuristic Search	p. 81
Proving Theorems in Geometry	p. 85
The General Problem Solver	p. 87
Game-Playing Programs	p. 89
Semantic Representations	p. 96
Solving Geometric Analogy Problems	p. 96
Storing Information and Answering Questions	p. 98
Semantic Networks	p. 100
Natural Language Processing	p. 103
Linguistic Levels	p. 103
Machine Translation	p. 107
Question Answering	p. 110
1960s' Infrastructure	p. 114
Programming Languages	p. 114
Early AI Laboratories	p. 115
Research Support	p. 118
All Dressed Up and Places to Go	p. 120
Efflorescence: MID-1960s to MID-1970s	p. 123
Computer Vision	p. 125
Hints from Biology	p. 126
Recognizing Faces	p. 127
Computer Vision of Three-Dimensional Solid Objects	p. 128
“Hand–Eye” Research	p. 141
At MIT	p. 141
At Stanford	p. 142
In Japan	p. 145
Edinburgh's “FREDDY”	p. 145
Knowledge Representation and Reasoning	p. 149
Deductions in Symbolic Logic	p. 149
The Situation Calculus	p. 152
Logic Programming	p. 153
Semantic Networks	p. 154
Scripts and Frames	p. 156
Mobile Robots	p. 162
Shakey, the SRI Robot	p. 162
The Stanford Cart	p. 176
Progress in Natural Language Processing	p. 181
Machine Translation	p. 181
Understanding	p. 182
Game Playing	p. 193
The Dendral Project	p. 197
Conferences, Books, and Funding	p. 202
Applications and Specializations: 1970s to early 1980s	p. 207
Speech Recognition and Understanding Systems	p. 209
Speech Processing	p. 209
The Speech Understanding Study Group	p. 211
The DARPA Speech Understanding Research Program	p. 212
Subsequent Work in Speech Recognition	p. 220
Consulting Systems	p. 224
The SRI Computer-Based Consultant	p. 224
Expert Systems	p. 229
Understanding Queries and Signals	p. 244
The Setting	p. 244
Natural Language Access to Computer Systems	p. 247
HASP/SIAP	p. 252
Progress in Computer Vision	p. 258
Beyond Line-Finding	p. 258
Finding Objects in Scenes	p. 262
DARPA's Image Understanding Program	p. 267
Boomtimes	p. 271
“New-Generation” projects	p. 275
The Japanese Create a Stir	p. 277
The Fifth-Generation Computer Systems Project	p. 277
Some Impacts of the Japanese Project	p. 281
DARPA's Strategic Computing Program	p. 286
The Strategic Computing Plan	p. 286
Major Projects	p. 289
AI Technology Base	p. 294
Assessment	p. 297
Entr'acte	p. 303
Speed Bumps	p. 305
Opinions from Various Onlookers	p. 305
Problems of Scale	p. 319
Acknowledged Shortcomings	p. 325
The “AI Winter”	p. 327
Controversies and Alternative Paradigms	p. 331
About Logic	p. 331
Uncertainty	p. 332
“Kludginess”	p. 333
About Behavior	p. 334
Brain-Style Computation	p. 339
Simulating Evolution	p. 341
Scaling Back AIs Goals	p. 344
The Growing Armamentarium: From the 1980s Onward	p. 347
Reasoning and Representation	p. 349
Nonmonotonic or Defeasible Reasoning	p. 349
Qualitative Reasoning	p. 352
Semantic Networks	p. 354
Other Approaches to Reasoning and Representation	p. 365
Solving Constraint Satisfaction Problems	p. 365
Solving Problems Using Propositional Logic	p. 368
Representing Text as Vectors	p. 373
Latent Semantic Analysis	p. 376
Bayesian Networks	p. 381
Representing Probabilities in Networks	p. 381
Automatic Construction of Bayesian Networks	p. 387
Probabilistic Relational Models	p. 391
Temporal Bayesian Networks	p. 393
Machine Learning	p. 398
Memory-Based Learning	p. 398
Case-Based Reasoning	p. 400
Decision Trees	p. 402
Neural Networks	p. 408
Unsupervised Learning	p. 413
Reinforcement Learning	p. 415
Enhancements	p. 422
Natural Languages and Natural Scenes	p. 431
Natural Language Processing	p. 431
Computer Vision	p. 436
Intelligent System Architectures	p. 455
Computational Architectures	p. 456
Cognitive Architectures	p. 467
Modern AI: Today And Tomorrow	p. 479
Extraordinary Achievements	p. 481
Games	p. 481
Robot Systems	p. 488
Ubiquitous Artificial Intelligence	p. 501
AI at Home	p. 501
Advanced Driver Assistance Systems	p. 502
Route Finding in Maps	p. 503
You Might Also Like…	p. 503
Computer Games	p. 504
Smart Tools	p. 507
In Medicine	p. 507
For Scheduling	p. 509
For Automated Trading	p. 509
In Business Practices	p. 510
In Translating Languages	p. 511
For Automating Invention	p. 511
For Recognizing Faces	p. 512
The Quest Continues	p. 515
In the Labs	p. 516
Toward Human-Level Artificial Intelligence	p. 525
Summing Up	p. 534
Index	p. 539
Table of Contents provided by Ingram. All Rights Reserved.

Nils J. Nilsson, Kumagai Professor of Engineering (Emeritus) in the Department of Computer Science at Stanford University, received his doctorate in electrical engineering from Stanford in 1958. He has served on the editorial boards of Artificial Intelligence and the Journal of Artificial Intelligence Research. He was also an area editor for the Journal of the Association for Computing Machinery. He is a past president and Fellow of the Association for the Advancement of Artificial Intelligence and a Fellow of the American Association for the Advancement of Science.

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