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 31
Nevertheless , the number of nodes expanded by an algorithm is one of the
factors that determines efficiency , and it is a factor that permits simple
comparisons . Suppose that A , is more informed than A , and that both A , and A ,
are versions ...
That is , if A * selects n for expansion , and if the monotone restriction is satisfied ,
g ( n ) = g * ( n ) . The monotone restriction also implies another interesting result ,
namely , that the f values of the sequence of nodes expanded by A * are ...
Since this fact is true for any adjacent pair of nodes in the sequence of nodes
expanded by A * , we have RESULT 8 : If the ... When the monotone restriction is
not satisfied , it is possible that some node has a smaller f value at expansion
What people are saying - Write a review
PRODUCTION SYSTEMS AND AI
SEARCH STRATEGIES FOR
10 other sections not shown