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 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.
Results 1-3 of 34
... precondition literals and if all of the mgu's are consistent ( that is , if these mgu's have a unifying composition ) . If such a match can be found , we say that the precondition of the F - rule matches the facts . We call the unifying ...
... precondition of F - rule 2 , and vice versa . They cannot both be first ! [ Sacerdoti ( 1977 ) called this type of ... precondition , CONT ( X , A ) , of F - rule 1 by F - rule 2. In this manner , DCOMP is led to continue the search for ...
... precondition is always postponed until the next lower level . We call these preconditions P - conditions . This scheme allows us to specify , for each F - rule , which preconditions are the most important ( to be achieved during the ...
PRODUCTION Systems and AI
SEARCH Strategies FOR
10 other sections not shown