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.
As we have already mentioned, AI methods and techniques have been applied in several different problem areas. To help motivate our subsequent discussions, we next describe some of these applications. 0.1. SOME APPLICATIONS OF ARTIFICIAL ...
This hypothesize-and-test paradigm is applied at many levels of the perception process. Several aligned segments suggest a straight line; a line detector can be employed to test it. Adjacent rectangles suggest the faces of a solid ...
A special detector, applied to the scene, confirms this expectation, thus raising confidence in the window hypothesis. We discuss some of the fundamental ideas underlying frame-structured representations and inference processes later in ...
The control system chooses which applicable rule should be applied and ceases computation when a termination condition on the global database is satisfied. There are several differences between this production system structure and ...
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 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