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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The control system chooses which applicable rule should be applied and ceases computation when a termination condition on the global database is satisfied.
A further generalization is to specify some true/false condition on states ... The problem goal condition forms the basis for the termination condition of ...
Procedure PRODUCTION 1 DATA - initial database 2 until DATA satisfies the termination condition, do: 3 begin 4 select some rule, R, in the set of rules that ...
Our hill-climbing function must be such that it attains its highest value for a database satisfying the termination condition. Applying hill-climbing to the ...
A graph-search control strategy grows such a tree until a database is produced that satisfies the termination condition. In Figure 1.4, we show all ...
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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