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Fuzzy reasoning : the integration of vague information.
Abstract
Thesis (Ph. D.)--John Hopkins University, 1976. Includes bibliographical references (leaves 90-95). Photocopy.
The paper presents the literature related to application of fuzzy set theory to Human Factors and has 784 research papers listed in the bibliography which is given at the end. As in any other collection this literature list has a subjective viewpoint and may be in some sense incomplete. Analysis of these data provides interesting insights regarding the characteristics of articles of the applications of fuzzy set theory, literature trends and the future. This paper consists of two parts. In Part I, the methodology used to gather the information, language, citation, and descriptor analysis, and conclusions are described. Part II is the main bibliography.
The application of dynamic programming to the modeling of decision control problems arising in research and development systems management is discussed. Probabilistic models for treating an allocation problem in the context of an antiballistic missile system are first reviewed in order to set the background for the use of fuzzy sets. Fuzzy research and development (R&D) systems are exemplified in the context of allocation problems occurring in cancer research appropriation. By recourse to fuzzy set theory, fuzzy dynamic programming models with their corresponding flow charts are then developed for an allocation problem arising in R&D systems. It is argued that the use of fuzzy set theory will generally provide models of better proximity to the systems modeled than the traditional deterministic and stochastic approaches. The computational problems in fuzzy algorithms are discussed. A method for deriving the membership function values is also presented. An example of the use of the digital computer to derive computational results from the models is presented.
The main part of the paper consists of a bibliography of some 1150 items, each keyword-indexed with some 750 being classified as concerned with fuzzy system theory and its applications. The remaining items are concerned with closely related topics in many-valued logic, linguistics, the philosophy of vagueness, etc. These background references are annotated in an initial section that outlines the relationship of fuzzy system theory to other developments and provides pointers to various possible fruitful interrelationships. Topics covered include: the philosophy and logic of imprecision and vagueness; other non-standard logics; foundations of set theory; probability theory; fuzzification of mathematical systems; linguistics and psychology; and applications.
The applicability of fuzzy set theory to decision analysis (DA) is examined. It extends the ideas of an earlier paper "Fuzzy decision analysis," by Watson et al. [33]. Particular emphasis is placed on justifying the use of Zadeh's fuzzy calculus to model impression, and an axiomatic system is suggested towards this end. This is seen as an attempt at extending Savage's axioms of subjective probability to produce "approximate probabilities." It is argued that the method proposed by Watson et al. for comparing decision options is unsatisfactory, and several alternative methods are developed. Some computational anomalies are pointed out which severely limit the potential of this methodology. It is suggested that, for individual decisionmaking, fuzzy decision analysis should be viewed as an automatic sensitivity analysis, but that fuzzy sets may be useful with another interpretation for group decisionmaking. The conclusions are that the methodology has too many limitations to be of use for isolated decisions but that it may have a value for often repeated generic decisions.
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