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.
Fundamental to the development of such systems are certain AI ideas about structures for representing contextual knowledge and certain techniques for making inferences from that knowledge. Although we do not treat the ...
How common knowledge should be represented and used is one of the system design problems that invites the methods of ... A key problem in the development of expert consulting systems is how to represent and use the knowledge that human ...
The ultimate goal is to represent the scene by some appropriate model. This model might consist of a high-level description such as “A hill with a tree on top with cattle grazing.” The point of the whole perception process is to produce ...
Usually there are several ways to so represent a problem. Selecting a good representation is one of the important arts involved in applying AI techniques to practical problems. For the 8-puzzle and certain other problems, we can easily ...
It also keeps track of the rules that have been applied so that it can compose them into the sequence representing the problem solution. In certain problems, we want the solution to be subject to certain additional constraints.
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CHAPTER 2 SEARCH STRATEGIES FOR AI PRODUCTION SYSTEMS
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