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. |
From inside the book
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... solving strategy. It has been found that it is often much more efficient to produce an inexpensive, errorful solution to a programming or robot control problem and then modify it (to make it work correctly), than to insist on a first ...
... solving NP-complete problems grows exponentially with problem size. It is not yet known whether faster methods (involving only polynomial time, say) exist, but it has been proven that if a faster method exists for one of the NP-complete ...
... solving in AI concentrates on search methods and applications of resolution theorem proving. An introductory book by Jackson (1974) treats these problem-solving ideas and also describes applications to natural language processing and ...
... solving from an AI perspective is the book by Newell and Simon (1972). The book edited by Norman and Rumelhart (1975) contains articles describing computer models of human memory, and a psychology text by Lindsay and Norman (1972) is ...
... the book by Aho, Hopcroft, and Ullman (1974). Lauriere (1978) presents a computer language and a system for solving combinatorial problems using AI methods. 0.3.8. PERCEPTION PROBLEMS Many good papers on the problems of 14 PROLOGUE.
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 |