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Foundations of Knowledge Acquisition - Machine Learning (Paperback, Softcover reprint of the original 1st ed. 1993)
Loot Price: R4,458
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Foundations of Knowledge Acquisition - Machine Learning (Paperback, Softcover reprint of the original 1st ed. 1993)
Series: The Springer International Series in Engineering and Computer Science, 195
Expected to ship within 10 - 15 working days
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The two volumes of Foundations of Knowledge Acquisition document
the recent progress of basic research in knowledge acquisition
sponsored by the Office of Naval Research. This volume is subtitled
Machine Learning, and there is a companion volume subtitled
Cognitive Models of Complex Learning. Funding was provided by a
five-year Accelerated Research Initiative (ARI), and made possible
significant advances in the scientific understanding of how
machines and humans can acquire new knowledge so as to exhibit
improved problem-solving behavior. Significant progress in machine
learning is reported along a variety of fronts. Chapters in Machine
Learning include work in analogical reasoning; induction and
discovery; learning and planning; learning by competition, using
genetic algorithms; and theoretical limitations. Knowledge
acquisition as pursued under the ARI was a coordinated research
thrust into both machine learning and human learning. Chapters in
Cognitive Modles of Complex Learning, also published by Kluwer
Academic Publishers, include summaries of work by cognitive
scientists who do computational modeling of human learning.In fact,
an accomplishment of research previously sponsored by ONR's
Cognitive Science Program was insight into the knowledge and skills
that distinguish human novices from human experts in various
domains; the Cognitive interest in the ARI was then to characterize
how the transition from novice to expert actually takes place.
These volumes of Foundations of Knowledge Acquisition serve as
excellent reference sources by bringing together descriptions of
recent and on-going research at the forefront of progress in one of
the most challenging arenas of artificial intelligence and
cognitive science. In addition, contributing authors comment on
exciting future directions for research.
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