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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... solve a simple puzzle. 1.1.1. THE 8-PUZZLE Many AI applications involve composing a sequence of operations. Controlling the actions of a robot and automatic programming are two examples. A simple and perhaps familiar problem of this ...
... solve a problem using a production system, we must specify the global database, the rules, and the control strategy. Transforming a problem statement into these three components of a production system is often called the representation ...
... . THE BASIC PROCEDURE The basic production system algorithm for solving a problem like the 8-puzzle can be written in nondeterministic form as follows: Procedure PRODUCTION 1 DATA - initial database 2 until DATA 20 PRODUCTION SYSTEMS AND ...
... solve problems requiring search. Trial-and-error methods seem to be inherent in solving puzzles, for example. One might argue that if a control strategy of a production system possessed sufficient knowledge about a puzzle to select ...
... solving this puzzle. The value of our hill-climbing function for each state description is circled. The figure shows that one of the rule applications along the path did not increase the value of our function. If none of the applicable ...
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 |