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.
Results 1-5 of 64
Control Knowledge For Rule-Based Deduction Systems 257 6.7. Bibliographical and Historical Remarks 267 Exercises 270 CHAPTER 7: BASIC PLAN-GENERATING ...
Knowledge Acquisition 419 10.3. Representational Formalisms 422 BIBLIOGRAPHY 429 AUTHOR INDEX 467 SUBJECT INDEX 471 PREFACE Previous treatments of ...
... 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.
... resources and shared knowledge to generate and understand highly condensed and streamlined messages: A word to the wise from the wise is sufficient.
Fundamental to the development of such systems are certain AI ideas about structures for representing contextual knowledge and certain techniques for making ...
What people are saying - Write a review
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