| 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. |
