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Books > Business & Economics > Business & management > Management & management techniques > Management decision making
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Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference (Hardcover, 1995 ed.)
Loot Price: R4,558
Discovery Miles 45 580
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Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference (Hardcover, 1995 ed.)
Series: Theory and Decision Library B, 30
Expected to ship within 10 - 15 working days
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With the vision that machines can be rendered smarter, we have
witnessed for more than a decade tremendous engineering efforts to
implement intelligent sys tems. These attempts involve emulating
human reasoning, and researchers have tried to model such reasoning
from various points of view. But we know precious little about
human reasoning processes, learning mechanisms and the like, and in
particular about reasoning with limited, imprecise knowledge. In a
sense, intelligent systems are machines which use the most general
form of human knowledge together with human reasoning capability to
reach decisions. Thus the general problem of reasoning with
knowledge is the core of design methodology. The attempt to use
human knowledge in its most natural sense, that is, through
linguistic descriptions, is novel and controversial. The novelty
lies in the recognition of a new type of un certainty, namely
fuzziness in natural language, and the controversality lies in the
mathematical modeling process. As R. Bellman [7] once said,
decision making under uncertainty is one of the attributes of human
intelligence. When uncertainty is understood as the impossi bility
to predict occurrences of events, the context is familiar to
statisticians. As such, efforts to use probability theory as an
essential tool for building intelligent systems have been pursued
(Pearl [203], Neapolitan [182)). The methodology seems alright if
the uncertain knowledge in a given problem can be modeled as
probability measures.
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