Principles of Artificial IntelligenceA 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 5
We now show that given a rather mild and reasonable restriction on h, when A*
selects a node for expansion it has ... A heuristic function, h, is said to satisfy the
monotone restriction if for all nodes n, and n, such that n, is a successor of n, h (ni
) ...
Using the monotone restriction, we have that g*(ni) + h (ni) < g”(ni) + c (ni, n +1) +
h(n +, ). Since ni and ni + are on an optimal path g*(n+1) = g”(ni) + c (ni, n +1),
therefore [g *(ni) + h (ni)] = [g”(n +1) + h(n +4)]. By transitivity, we then have ...
When the monotone restriction is not satisfied, it is possible that some node has a
smaller f value at expansion than that of a previously expanded node. We can
exploit this observation to improve the efficiency of A* under this condition.
You have reached your viewing limit for this book.
You have reached your viewing limit for this book.
What people are saying - Write a review
Contents
| 1 | |
| 17 | |
| 53 | |
CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS | 99 |
CHAPTER 4 THE PREDICATE CALCULUS IN AI | 131 |
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS | 161 |
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS | 193 |
CHAPTER 7 BASIC PLANGENERATING SYSTEMS | 275 |
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS | 321 |
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS | 361 |
PROSPECTUS | 417 |
BIBLIOGRAPHY | 429 |
AUTHOR INDEX | 467 |
SUBJECT INDEX | 471 |
Other editions - View all
Common terms and phrases
Bibliographic information
| Title | Principles of Artificial Intelligence |
| Author | Nils J. Nilsson |
| Edition | reprint |
| Publisher | Morgan Kaufmann, 2014 |
| ISBN | 1483295869, 9781483295862 |
| Length | 476 pages |
| Subjects | › Computers / Data Processing Computers / Expert Systems Computers / General Computers / Intelligence (AI) & Semantics |
| Export Citation | BiBTeX EndNote RefMan |