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.
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It seems more reasonable to think of a delineation unit as a special form of
implicational rule . Delineation units can be used in the forward direction to
create new fact units or to add properties to existing fact units . For example ,
suppose we ...
Applying the delineation unit to the fact unit involves adding , to the fact unit , the
slots " major : CS ” and “ class : GRAD . ” Thus extended , the fact unit JOHN
matches our goal unit JOHN . Used in the backward direction on the goal unit ,
antecedent ( ANTE ) and consequent ( CONSE ) are lists of units ( possibly
containing variables ) . When a unit rule is used in the forward direction , if all of
the units in the ANTE ( regarded as goal units ) are matched by fact units , then
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