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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Nils J. Nilsson. Several of these problems (including the traveling salesman problem) are members of a class that ... solving NP-complete problems grows exponentially with problem size. It is not yet known whether faster methods ...
... problem 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 ...
... problem solving from an AI perspective is the book by Newell and Simon (1972). The book edited by Norman and ... problems in natural language processing. A collection of important papers on this topic is contained in a book edited by ...
... problem state, namely, the goal state shown in Figure 1.1. We can also deal with problems for which the goal is to ... solving a problem like the 8-puzzle can be written in nondeterministic form as follows: Procedure PRODUCTION 1 DATA ...
... solving the 8-puzzle problem posed in Figure 1.1. We can keep track of the various rules applied and the databases produced by a structure called a search tree. An example of such a tree is in Figure 1.4. At the top or root of the tree ...
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 |