Fuzzy Rationality, Ambiguity and Risk in Decision-Choice Process
In chapter One of this monograph we dealt with the nature of fuzzy optimal rationality as it relates to uncertainty and expectation formation of decision-choice agents. This fuzzy rationality is also intended to resolve the problems of vagueness and ambiguity that produce contradiction. Total uncertainty in the decision-choice processes including knowledge construct was separated into probabilistic and possibilistic uncertainties. Both uncertainties relate to cognition. The probabilistic uncertainty is due to knowledge limitativeness and limitationality in the decision-choice process. The probability space is said to be limitational (limitative) if a knowledge production is necessary (sufficient) condition to reduce uncertainty and hence increase probabilistic belief of decision-choice outcome. The possibilistic uncertainty is due to the presence of vagueness (broadly defined) that includes blurredness and penumbral regions in knowledge, language and linguistic reasoning in the decision-choice process. This knowledge constraint is due to the idea that in all decision-choice circumstances knowledge is incomplete and provisional, whose acceptance is based on socially acceptable methods of knowledge production. Expectation formation has traditionally been linked with stochastic uncertainty and our discussion on the subject maintained the traditional connection between expectation formation and probabilistic uncertainty. This allows us to discuss the cognitive relationship between probability and the measure of ignorance. In general the circumference of expectation formation must be span by the diameter of total uncertainty of both probabilistic and possibilistic nature. The mathematical and logical tradition is such that the possibilistic characteristics are neglected or done away by assumption in the sense that what we know is exact.
KeywordsKnowledge Structure Optimal Rationality Fuzzy Rationality Classical Paradigm Penumbral Region
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