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.
... has been the notion of debugging as a problem-solving strategy. ... errorful solution to a programming or robot control problem and then modify it (to ...
... that might be called a global database that is manipulated by certain well-defined operations, all under the control of some global control strategy.
To solve a problem using a production system, we must specify the global database, the rules, and the control strategy. Transforming a problem statement ...
The control strategy repeatedly applies rules to state descriptions until a description of a goal state is produced. It also keeps track of the rules that ...
Selecting rules and keeping track of those sequences of rules already tried and the databases they produced constitute what we call the control strategy for ...
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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