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
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... search and breadth - first search . The first type of uninformed search orders the nodes on OPEN in descending order of their depth in the search tree . The deepest nodes are put first in the list . Nodes of equal depth are ordered ...
... depth - first procedure generates new databases in an order similar to that generated by an uninformed backtracking control strategy . The correspondence would be exact if the graph - search process generated only one successor at a ...
Nils J. Nilsson. Branching factor , of search processes , 92-94 Breadth - first search , 69-71 Breadth - first strategy , in resolution , 165-166 CANCEL relation , in theorem proving , 254-257 , 270 Candidate solution graph , 217-218 ...
Contents
PROLOGUE | 1 |
PRODUCTION Systems and AI | 17 |
SEARCH Strategies FOR | 53 |
Copyright | |
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