Principles of Artificial Intelligence
A 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.
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Control Knowledge For Rule-Based Deduction Systems 257 6.7. Bibliographical and Historical Remarks 267 Exercises 270 CHAPTER 7: BASIC PLAN-GENERATING SYSTEMS 275 Robot Problem Solving 275 A Forward Production System 281 A Representation ...
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.
It is assumed that the reader has a good background in the fundamentals of computer science; knowledge of a list-processing language, such as LISP, would be helpful. A course organized around this book could comfortably occupy a full ...
The evolution of language use has apparently exploited the opportunity for participants to use their considerable computational resources and shared knowledge to generate and understand highly condensed and streamlined messages: A word ...
A computer system capable of understanding a message in natural language would seem, then, to require (no less than would a human) both the contextual knowledge and the processes for making the inferences (from this contextual knowledge ...
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CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS
CHAPTER 4 THE PREDICATE CALCULUS IN AI
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS
CHAPTER 7 BASIC PLANGENERATING SYSTEMS
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS