Difference between revisions of "Fuzzy Logic"
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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 imprecisionand approximate reasoning. More speciﬁcally, fuzzy logic may be viewed as anattempt at formalization/mechanization of two remarkable human capabilities.
Academia Letters, January 2021
Kevin Willison, firstname.lastname@example.org
Willison, K. (2021). Dual-Process Models in Sociology: Reﬂections and Potential. Academia Letters
. 3 ©2021 by Academia Inc. — Open Access — Distributed under CC BY 4.0
First, the capability to converse, reason and make rational decisions in an envi-ronment of imprecision, uncertainty, incompleteness of information, conﬂictinginformation, partiality of truth and partiality of possibility – in short, in an envi-ronment of imperfect information. And second, the capability to perform a widevarietyofphysicalandmentaltaskswithoutanymeasurementsandanycomputa-tions,fromcomputingwithnumberstocomputingwithwords-frommanipulationof measurements to manipulation of perceptions ” (Zadeh,2008:2751).According to Turner (2021) “Dual process models in sociology are faced with a genericproblem of computationalist approaches to cognitive science about generalization: if the pro-cesses 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, amongits varied attributes, fuzzy logic has a high power of cointensive precisiation. Informally, pre-cisiation is an operation which transforms an object, p into an object, p*, which in somespeciﬁed sense is deﬁned more precisely than p (Zadeh, 2008). This power is needed fora formulation of cointensive deﬁnitions of scientiﬁc concepts and cointensive formalizationof human-centric ﬁelds such as economics, linguistics, law, conﬂict resolution, psychologyand medicine (Zadeh, 2008). Like all constructs of knowledge fuzzy logic has its limitationsbut 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