Difference between revisions of "Fuzzy Logic"

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[[Category: Logic]]
[[Category: Philosophy]]

Revision as of 10:29, 19 December 2021

Full Title or Meme

A logic that goes beyond the two-valued "true" and "false" of Boolean logic to a continuum, which could be imaged as a probability of 0 to 1.


As described in brief by the developer of fuzzy logic, Lotfi Zadeh:“ Fuzzy logic is not fuzzy. Basically, fuzzy logic is a precise logic of imprecision and approximate reasoning. More specifically, fuzzy logic may be viewed as an attempt at formalization/mechanization of two remarkable human capabilities.

Academia Letters, January 2021

Corresponding Author:

Kevin Willison, kdwillis@lakeheadu.ca


Willison, K. (2021). Dual-Process Models in Sociology: Reflections and Potential.
Academia Letters,Article 201.

First, the capability to converse, reason and make rational decisions in an environment of imprecision, uncertainty, incompleteness of information, conflicting information, partiality of truth and partiality of possibility – in short, in an environment of imperfect information. And second, the capability to perform a wide variety of physical and mental tasks without any measurements and any computations, fromc omputing with numbers to computing with words-from manipulation of measurements to manipulation of perceptions ” (Zadeh,2008:2751). According to Turner (2021) “Dual process models in sociology are faced with a generic problem of computationalist approaches to cognitive science about generalization: if the processes are machine or computer-like, these processes don’t generalize to near cases very well. The idea that fuzzy logic might help is a reasonable response to this problem.” Indeed, among its varied attributes, fuzzy logic has a high power of cointensive precisiation. Informally, precisiation is an operation which transforms an object, p into an object, p*, which in some specified sense is defined more precisely than p (Zadeh, 2008). This power is needed fora formulation of cointensive definitions of scientific concepts and cointensive formalization of human-centric fields such as economics, linguistics, law, conflict resolution, psychology and medicine (Zadeh, 2008). Like all constructs of knowledge fuzzy logic has its limitations but its adaptability to be used in a wide array of applications garners support that such holdspotential to effectively serve to augment dual- process modelling initiatives. The potentialbenefit of fuzzy logic to that of sociology and the social sciences in general may be examinedfurther in Kosko (1999, 1994); Bunge (1983); and Uddin (2017).As quoted by Edgar Degas: “Art is not what you see but what you make others see”(Schenkel, 2004). By replacing the word “art”, this same line of thinking may hold as a goalof theory. In so doing, new creative approaches and added bridges are enabled to help connectexisting and developing disciplines, plus constructs of knowing in general. To this end andbeyond, dual-process models hold potential to further expand our thinking, or as Leschziner(2019) would say, help explicate social action. Finding new in-roads towards this quest suchasthepotentialincorporationoffuzzylogic, requiresthatwesharpenourcreativity(Willison,2017), curiosity and sociological imagination (Mills, 1959).Overall, the domain of sociology has expanded by an emphasis on integrative practicesas we witness and benefit from such emerging fields as: cognitive sociology, environmentalsociology, computational sociology and sociological social psychology, and so forth, to namebut a few relatively new developments. As indicated by Henry (2021), the importance of incorporating an interdis