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 6-10 of 85
... 417 10.1. AI System Architectures 418 10.2. Knowledge Acquisition 419 10.3. Representational Formalisms 422 BIBLIOGRAPHY 429 AUTHOR INDEX 467 SUBJECT INDEX 471 PREFACE Previous treatments of Artificial Intelligence (AI) divide the subject.
... intelligent data retrieval systems, etc. The major difficulty with this approach is that these application areas are now ... Artificial Intelligence, are covered here as well, this book contains many additional topics such as rule-based ...
... Artificial Intelligence Center at SRI. One could not find a more dynamic, intellectually stimulating, and constructively critical setting in which to work and write. Though this book carries the name of a single author, it has been ...
... artificial intelligence. Most of the work on building these kinds of systems has taken place in the field called Artificial Intelligence (AI). This work has had largely an empirical and engineering orientation. Drawing from a loosely ...
... sufficient. Thus generating and understanding language is an encoding and decoding problem of fantastic complexity. A computer system capable of understanding a message in natural 2 PROLOGUE 0.1. Some Applications of Artificial ...
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 |