Previous treatments of Artificial Intelligence (AI) divide the
subject into its major areas of application, namely, natural
language processing, automatic programming, robotics, machine
vision, automatic theorem proving, intelligent data retrieval
systems, etc. The major difficulty with this approach is that these
application areas are now so extensive, that each could, at best,
be only superficially treated in a book of this length. Instead, I
have attempted here to describe fundamental AI ideas that underlie
many of these applications. My organization of these ideas is not,
then, based on the subject matter of their application, but is,
instead, based on general computational concepts involving the
kinds of data structures used, the types of operations performed on
these data struc tures, and the properties of con'trol strategies
used by AI systems. I stress, in particular, the important roles
played in AI by generalized production systems and the predicate
calculus. The notes on which the book is based evolved in courses
and seminars at Stanford University and at the University of
Massachusetts at Amherst. Although certain topics treated in my
previous book, Problem solving Methods in Artificial Intelligence,
are covered here as well, this book contains many additional topics
such as rule-based systems, robot problem-solving systems, and
structured-object representations."
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