Fuzzy decision making under transition from silence to confusion

• Autorzy: Uemura Y.
• Języki publikacji: EN

Abstrakty

EN

Faculty of Education, Mie University, 1515 Kamihamacho, Isu; Mie, Japan uemura0742yahoo.co.jp We often fall into silence. After that, we make a decision through confusion, in most cases. In silence, cool mind runs parallel with warm heart. Traversing over these two, the phenomenon arises, chich can be interpreted as a fuzzy event, which can be called waver. In other words, two states of nature develop into conflict, and are covered by a fuzzy event. In confusion, we consider that the states of nature, which had been moving in conflict, not only undergo an inversion, but also a transformation takes place from warm heart into dry mind. It is therefore possible to derive a fuzzy function, resulting from the fuzzification of the transition matrix from silence to confusion, absorbing noise, and taking expectation to link the membership function with the multi-attribute utility function. This short note shows that we can calculate the expected utility by using both the probability of a fuzzy. event and the subjective importance of the two states of nature for the decision maker. Further, we can obtain an optimum action, based on the theory of maximum expected utility.

Słowa kluczowe

EN

fuzzy event; expected utility; decision making; silence; confusion

• Wydawca: Systems Research Institute, Polish Academy of Sciences
• Czasopismo: Control and Cybernetics
• Rocznik: 2015
• Tom: Vol. 44, no. 3
• Strony: 407--411
• Opis fizyczny: Bibliogr. 7 poz., rys.

Twórcy

autor

Uemura Y.

• Faculty of Education, Mie University, 1515 Kamihamacho, Isu; Mie, Japan

Bibliografia

• [1] Tanaka, H. and Iwabuchi, H. (1992) A Theory of Evidence Using Normal Possibility Theory. J. of Systems, Control and Information Engineers, 5, 243-253 (in Japanese).
• [2] Tanaka, H., Okuda, T. and Asai K. (1976) Fuzzy Decision Problems and Information. J. of the Society of Instrument and Control Engineers, 12, 63-68 (in Japanese).
• [3] Uemura, Y. (1991) A decision rule on a fuzzy event. Japanese Journal of Fuzzy Theory and Systems, 3, 123-130 (in Japanese).
• [4] Uemura, Y. (1995) A normal possibility decision rule. Control and Cybernetics, 24, 233-238.
• [5] Uemura, Y. (2001) Application of normal possibility theory to silence. Control and Cybernetics, 30, 465-472.
• [6] Uemura, Y. and Sakawa, M. (1993) A simple decision rule on possibility distribution of fuzzy events. Japanese Journal of Fuzzy Theory and Systems, 5, 528-536 (in Japanese).
• [7] Zadeh, L. A. (1968) Probability measure of a fuzzy event. J. of Mathematical Analysis and Applications, 22, 421-427.