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 Intelligence"evolved 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 1-3 of 72
Thus , we have : RESULT 2 : At any time before A * terminates , there exists on
OPEN a node n ' that is on an optimal path from s to a goal node , with f ( n ) = f * (
s ) . Combining this result with our previous argument , that even the smallest f ...
is a goal node , we have f ( n ) = f * ( s ) by RESULT 4 ; so suppose n is not a goal
node . Now A * selected n 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 ...
Nils J. Nilsson. f ( ng ) = 8 ( ng ) + hing ) = g * ( ng ) + hing ) ( RESULT 7 ) = g * ( ni
) + c ( n , ng ) + hing ) g ( nh ) + c ( a , n ) + ( RESULT 7 ) ( n ) Since the monotone
restriction implies c ( a , n ) + n ( n ) = ( nh ) , we have f ( ne ) > 8 ( ni ) + h ( n . ) ...
What people are saying - Write a review
PRODUCTION SYSTEMS AND AI
SEARCH STRATEGIES FOR
10 other sections not shown