Principles of Artificial Intelligence
Morgan Kaufmann, Jun 28, 2014 - Computers - 476 pages
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.
From inside the book
Results 1-5 of 56
... 53 Backtracking Strategies 55 Graph-search Strategies 61 Uninformed Graph-search Procedures 68 Heuristic Graph-search Procedures 72 Related Algorithms 88 Measures of Performance 91 Bibliographical and Historical Remarks 94 Exercises ...
Chapter 2 concerns itself with heuristic methods for searching the graphs that are implicitly defined by many AI systems. Chapter 3 generalizes these search techniques to extended versions of these graphs, called AND/OR graphs, ...
For each class of integrand, the various rules were selected according to their heuristic applicability. In Figure 1.13 we show an AND/OR tree that illustrates a possible search performed by a decomposable production system.
The literature on heuristic graph searching is extensive; several references are cited in the next two chapters. 1.4.3, EXAMPLE PROBLEMS Problem-solving programs have sharpened their techniques on a variety of puzzles and games.
3 RULES - APPRULES(DATA); APPRULES is a function that computes the rules applicable to its argument and orders them (either arbitrarily or according to heuristic merit). 4 LOOP: if NULL(RULES), return FAIL; if there are no (more) rules ...
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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