Uncertain Computation-Based Decision Theory

By: Rafik Aziz Aliev

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eText | 6 December 2017

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Uncertain computation is a system of computation and reasoning in which the objects of computation are not values of variables but restrictions on values of variables.

This compendium includes uncertain computation examples based on interval arithmetic, probabilistic arithmetic, fuzzy arithmetic, Z-number arithmetic, and arithmetic with geometric primitives.

The principal problem with the existing decision theories is that they do not have capabilities to deal with such environment. Up to now, no books where decision theories based on all generalizations level of information are considered. Thus, this self-containing volume intends to overcome this gap between real-world settings' decisions and their formal analysis.

Contents:

Decision Environment
Analysis of the Existing Decision Theories
Interval Computation
Probabilistic Arithmetic
Fuzzy Type-1 and Fuzzy Type-2 Computations
Computation with Z-Numbers
Computation with U-Numbers
Fuzzy Geometry Based Computations
Interval Granular-Based Decision Making
Decision Making in Fuzzy Environment
The Z-Restriction Centered Decision Theory
Simulation and Applications

Readership: Researchers, academics, professionals and graduate students in fuzzy logic, decision sciences and mathematical economics.
Keywords:Uncertain Computation;Decision Making;Interval Arithmetic;Fuzzy Arithmetic;Z-Number;Combined State;Fuzzy EconomicsReview:0