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Books > Computing & IT > Applications of computing > Artificial intelligence
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The Metaphysical Nature of the Non-adequacy Claim - An Epistemological Analysis of the Debate on Probability in Artificial Intelligence (Paperback, 2013 ed.)
Loot Price: R3,269
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The Metaphysical Nature of the Non-adequacy Claim - An Epistemological Analysis of the Debate on Probability in Artificial Intelligence (Paperback, 2013 ed.)
Series: Studies in Computational Intelligence, 464
Expected to ship within 10 - 15 working days
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Over the last two decades, the field of artificial intelligence has
experienced a separation into two schools that hold opposite
opinions on how uncertainty should be treated. This separation is
the result of a debate that began at the end of the 1960's when AI
first faced the problem of building machines required to make
decisions and act in the real world. This debate witnessed the
contraposition between the mainstream school, which relied on
probability for handling uncertainty, and an alternative school,
which criticized the adequacy of probability in AI applications and
developed alternative formalisms. The debate has focused on the
technical aspects of the criticisms raised against probability
while neglecting an important element of contrast. This element is
of an epistemological nature, and is therefore exquisitely
philosophical. In this book, the historical context in which the
debate on probability developed is presented and the key components
of the technical criticisms therein are illustrated. By referring
to the original texts, the epistemological element that has been
neglected in the debate is analyzed in detail. Through a
philosophical analysis of the epistemological element it is argued
that this element is metaphysical in Popper's sense. It is shown
that this element cannot be tested nor possibly disproved on the
basis of experience and is therefore extra-scientific. Ii is
established that a philosophical analysis is now compelling in
order to both solve the problematic division that characterizes the
uncertainty field and to secure the foundations of the field
itself.
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