Every day decision making and decision making in complex
human-centric systems are characterized by imperfect
decision-relevant information. Main drawback of the existing
decision theories is namely incapability to deal with imperfect
information and modeling vague preferences. Actually, a paradigm of
non-numerical probabilities in decision making has a long history
and arose also in Keynes's analysis of uncertainty. There is a need
for further generalization - a move to decision theories with
perception-based imperfect information described in NL. The
languages of new decision models for human-centric systems should
be not languages based on binary logic but human-centric
computational schemes able to operate on NL-described information.
Development of new theories is now possible due to an increased
computational power of information processing systems which allows
for computations with imperfect information, particularly,
imprecise and partially true information, which are much more
complex than computations over numbers and probabilities.
The monograph exposes the foundations of a new decision theory
with imperfect decision-relevant information on environment and a
decision maker's behavior. This theory is based on the synthesis of
the fuzzy sets theory with perception-based information and the
probability theory.
The book is self containing and represents in a systematic way
the decision theory with imperfect information into the educational
systems. The book will be helpful for teachers and students of
universities and colleges, for managers and specialists from
various fields of business and economics, production and social
sphere.
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