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. |
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... result with our previous argument , that even the smallest ƒ values of the nodes on OPEN of a nonterminating A * become unbounded , shows that A * must terminate even for infinite graphs . Thus , RESULT 3 : If there is a path from s to ...
... RESULT 4 ; so suppose n is not a goal node . Now A * selected ʼn before termination , so at this time ( by RESULT 2 ) we know that there existed on OPEN some node n ' on an optimal path from s to a goal with f ( n ' ) ≤ f * ( s ) . If ...
... ( RESULT 7 ) = g * ( n1 ) + c ( n1 , ng ) + h ( n , ) = g ( n ) + c ( ni , ng ) + h ( ng ) ( RESULT 7 ) Since the monotone restriction implies c ( ni , ng ) + h ( ng ) > h ( n ) , we have f ( ng ) > g ( nı ) + h ( n ) = f ( n ) . Since ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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