The Quest for Artificial IntelligenceArtificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today's AI engineers. AI is becoming more and more a part of everyone's life. The technology is already embedded in face-recognizing cameras, speech-recognition software, Internet search engines, and health-care robots, among other applications. The book's many diagrams and easy-to-understand descriptions of AI programs will help the casual reader gain an understanding of how these and other AI systems actually work. Its thorough (but unobtrusive) end-of-chapter notes containing citations to important source materials will be of great use to AI scholars and researchers. This book promises to be the definitive history of a field that has captivated the imaginations of scientists, philosophers, and writers for centuries. |
Contents
Consulting Systems | |
Understanding Queries and Signals | |
Progress in Computer Vision | |
Boomtimes | |
The Japanese Create a Stir | |
DARPAs Strategic Computing Program | |
Speed Bumps | |
FROM THE 1980s ONWARD | |
Computer Vision | |
HandEye Research | |
Knowledge Representation and Reasoning | |
Mobile Robots | |
Progress in Natural Language Processing | |
Game Playing | |
Conferences Books and Funding | |
Speech Recognition and Understanding Systems | |
Other Approaches to Reasoning and Representation | |
Bayesian Networks | |
Natural Languages and Natural Scenes | |
Intelligent System Architectures | |
TODAY AND TOMORROW | |
Ubiquitous Artificial Intelligence | |
Other editions - View all
Common terms and phrases
ACT-R action AI’s algorithm Allen Newell applications architecture Artificial Intelligence Available online Bayesian networks behavior brain called Cambridge Carnegie Mellon University chess Classification cognitive Computer Science computer vision Conference configuration DARPA database defined DENDRAL described developed difficulties Donald Michie efficient Engineering example expert systems Feigenbaum field Figure final find first goal grammar heuristic human ideas IEEE inference input International John knowledge Laboratory later logical machine learning Marvin Minsky mathematical McCarthy methods natural language processing neural networks nodes objects office paper parse pattern recognition performance Ph.D Photograph courtesy Press probabilistic probability problem Proceedings proposed reasoning representation represented robot Ross Quinlan rules satisfied scene semantic networks sentences Shakey shown in Fig Simon simulation solve specific speech recognition speech understanding Stanford structure symbol tasks techniques theory translation tree University values vectors vehicles words wrote