By Rafik A Aliev, Oleg H Huseynov
Each day selection making in advanced human-centric structures are characterised by way of imperfect decision-relevant info. The crucial issues of the present selection theories are that they don't have strength to accommodate events within which possibilities and occasions are vague. during this publication, we describe a brand new conception of selection making with imperfect info. the purpose is to shift the basis of selection research and monetary habit from the world bivalent good judgment to the area fuzzy good judgment and Z-restriction, from exterior modeling of behavioral judgements to the framework of mixed states.
This publication might be worthwhile for pros, teachers, managers and graduate scholars in fuzzy good judgment, selection sciences, man made intelligence, mathematical economics, and computational economics.
Readership: execs, lecturers, managers and graduate scholars in fuzzy good judgment, determination sciences, synthetic intelligence, mathematical economics, and computational economics.
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Additional info for Decision Theory with Imperfect Information
Chapter 10 is devoted to decision making when relevant information is too vague to be precisiated (described) by fuzzy sets but stays at a level of image perceptions. Modeling of outstanding capability of humans to make decisions based on unprecisiated visual perceptions is a motivation of the research suggested in this chapter. Unprecisiated visual images are considered as information granules described by 2D convex sets. The length of a set is measured along the first dimension and represents an imprecision of perception-based information on a value of interest considered.
Indeed, these models are based on assumptions that people behave as 舖computational machines舗 functioning according to predefined mathematical algorithms. Of course, these don舗t correspond to the computational abilities of humans. g. humans either know actual probabilities or they can assign subjective probabilities to each outcome. Really, actual probabilities are very seldom known in real life, and the use of subjective probabilities is very often questionable or not compatible with human choices.
Furthermore, a so-called gain-loss asymmetry was observed: influence of losses on human choices dominates influence of gains. Humans舗 attitudes to risk depend on whether they deal with gains or losses. 200. e. they are risk averse. 2 In this case the choice of the majority of people was the opposite. 000 of certain loss. e. they are risk seeking dealing with losses. Based on the above mentioned evidence, Kahneman and Tversky concluded that the main factor that influences human choices in such experiments is loss aversion.
Decision Theory with Imperfect Information by Rafik A Aliev, Oleg H Huseynov