Principles of Artificial IntelligenceA classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of the control strategies used. Principles of Artificial Intelligenceevolved from the author's courses and seminars at Stanford University and University of Massachusetts, Amherst, and is suitable for text use in a senior or graduate AI course, or for individual study. |
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PREFACE Previous treatments of Artificial Intelligence (AI) divide the subject into
its major areas of application, namely, natural language processing, automatic
programming, robotics, machine vision, automatic theorem proving, intelligent ...
... mathematics, engaging in commonsense reasoning, understanding language,
and even driving an automobile are said to demand “intelligence. ... of specific
applications, such as automatic programming or natural language processing.
SOME APPLICATIONS OF ARTIFICIAL INTELLIGENCE 0.1.1. NATURAL
LANGUAGE PROCESSING When humans communicate with each other using
language, they employ, almost effortlessly, extremely complex and still little
understood ...
NATURAL LANGUAGE PROCESSING Grosz (1979) presents a good survey of
current techniques and problems in ... One of the first successful AI systems for
understanding limited fragments of natural language is described in a book by ...
interface systems for subsets of natural language are described in an article
edited by Waltz (1977). Proceedings of biannual conferences on Theoretical
Issues in Natural Language Processing (TINLAP) contain several important
papers.
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Contents
1 | |
17 | |
53 | |
CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS | 99 |
CHAPTER 4 THE PREDICATE CALCULUS IN AI | 131 |
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS | 161 |
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS | 193 |
CHAPTER 7 BASIC PLANGENERATING SYSTEMS | 275 |
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS | 321 |
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS | 361 |
PROSPECTUS | 417 |
BIBLIOGRAPHY | 429 |
AUTHOR INDEX | 467 |
SUBJECT INDEX | 471 |