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Real-world information is imperfect and is usually described in
natural language (NL). Moreover, this information is often
partially reliable and a degree of reliability is also expressed in
NL. In view of this, the concept of a Z-number is a more adequate
concept for the description of real-world information. The main
critical problem that naturally arises in processing
Z-numbers-based information is the computation with Z-numbers.
Nowadays, there is no arithmetic of Z-numbers suggested in existing
literature.This book is the first to present a comprehensive and
self-contained theory of Z-arithmetic and its applications. Many of
the concepts and techniques described in the book, with carefully
worked-out examples, are original and appear in the literature for
the first time.The book will be helpful for professionals,
academics, managers and graduate students in fuzzy logic, decision
sciences, artificial intelligence, mathematical economics, and
computational economics.
Every day decision making in complex human-centric systems are
characterized by imperfect decision-relevant information. The
principal problems with the existing decision theories are that
they do not have capability to deal with situations in which
probabilities and events are imprecise. In this book, we describe a
new theory of decision making with imperfect information. The aim
is to shift the foundation of decision analysis and economic
behavior from the realm bivalent logic to the realm fuzzy logic and
Z-restriction, from external modeling of behavioral decisions to
the framework of combined states.This book will be helpful for
professionals, academics, managers and graduate students in fuzzy
logic, decision sciences, artificial intelligence, mathematical
economics, and computational economics.
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