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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That is, if these systems are described at an appropriate level, one can often identify a central entity that might be called a global database that is ...
The production rules operate on the global database. Each rule has a precondition that is either satisfied or not by the global database.
To solve a problem using a production system, we must specify the global database, the rules, and the control strategy. Transforming a problem statement ...
We need only some real-valued function on the global databases. ... It selects (irrevocably) the applicable rule that produces a database giving 22 ...
Any global database beginning and ending with A and naming all of the other cities satisfies the termination condition. Notice that we can use the.
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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