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.
Results 1-5 of 34
... Bibliographical and Historical Remarks 48 Exercises 50 SEARCH STRATEGIES FOR AI PRODUCTION SYSTEMS 53 Backtracking Strategies 55 Graph-search Strategies ...
In one, which we call backtracking, a backtracking point is established when a rule is selected. Should subsequent computation encounter difficulty 21 ...
Should subsequent computation encounter difficulty in producing a solution, the state of the computation reverts to the previous backtracking point, ...
Backtracking. In many problems of interest, applying an inappropriate rule may prevent or substantially delay successful termination.
The backtracking process is one way in which the control strategy can be tentative. A rule is selected, and if it doesn't lead to a solution, ...
What people are saying - Write a review
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