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
Results 1-3 of 30
... direction , it is often convenient to make this distinction explicit . When a problem has intuitively clear states ... direction . The computational effort is the same for both directions . There are occasions , however , when it is more ...
... direction ) rules are applied to an initial global database consisting of the set { D , E , F , G } . ( We indicate a reverse direction application of rule R by R ' . ) We note that the production system that results from using these ...
... direction of rule application . The best direction in which to apply a rule sometimes depends on the domain . As an example of the importance of the direction in which a rule is applied , consider rules that express taxonomic ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
10 other sections not shown