Fuzzy concept

A fuzzy concept is an idea of which the boundaries of application can vary considerably according to context or conditions, instead of being fixed once and for all. This means the idea is somewhat <a href="/facts/Vagueness/BUlktmmr">vague</a> or imprecise. Yet it is not unclear or meaningless. It has a definite meaning, which can be made more exact only through further elaboration and specification — including a closer definition of the context in which the concept is used. 
The <a href="/facts/Colloquial/HvEweYjS">colloquial</a> meaning of a "fuzzy concept" is that of an idea which is "somewhat imprecise or vague" for any kind of reason, or which is "approximately true" in a situation. The inverse of a "fuzzy concept" is a "crisp concept" (i.e. a precise concept). Fuzzy concepts are often used to navigate imprecision in the real world, when precise information is not available, but where an indication is sufficient to be helpful.
Although the linguist <a href="/facts/George_Lakoff/gT0I0UNd">George Philip Lakoff</a> already defined the semantics of a fuzzy concept in 1973, inspired by an unpublished 1971 paper by <a href="/facts/Eleanor_Rosch/LvBgtCll">Eleanor Rosch</a>, the term "fuzzy concept" rarely received a standalone entry in dictionaries, handbooks and encyclopedias. Sometimes it was defined in encyclopedia articles on <a href="/facts/Fuzzy_logic/1PvN4Att">fuzzy logic</a>, or it was simply equated with a mathematical “<a href="/facts/Fuzzy_set/BGWudHJq">fuzzy set</a>”. A fuzzy concept can be "fuzzy" for many different reasons in different contexts. This makes it harder to provide a precise definition that covers all cases. Paradoxically, the definition of fuzzy concepts may itself be somewhat fuzzy.
With more academic literature on the subject, the term "fuzzy concept" is now widely recognized as a philosophical or scientific category, and the study of the characteristics of fuzzy concepts and fuzzy language is known as fuzzy semantics. “Fuzzy logic” has become a generic term for many different kinds of <a href="/facts/Many-valued_logic/qNI26RdF">many-valued logics</a>. <a href="/facts/Lotfi_A._Zadeh/WojTlG4Y">Lotfi A. Zadeh</a>, known as "the father of fuzzy logic", claimed that "vagueness connotes insufficient specificity, whereas fuzziness connotes unsharpness of class boundaries". Not all scholars agree.
For engineers, "Fuzziness is imprecision or vagueness of definition." For computer scientists, a fuzzy concept is an idea which is "to an extent applicable" in a situation. It means that the concept can have gradations of significance or unsharp (variable) boundaries of application — a "fuzzy statement" is a statement which is true "to some extent", and that extent can often be represented by a scaled value (a score). For mathematicians, a "fuzzy concept" is usually a <a href="/facts/Fuzzy_set/BGWudHJq">fuzzy set</a> or a combination of such sets (see <a href="/facts/Fuzzy_mathematics/DAdIA1HM">fuzzy mathematics</a> and <a href="/facts/Fuzzy_set_theory/BGWudHJq">fuzzy set theory</a>). In <a href="/facts/Cognitive_linguistics/Qu4DApFf">cognitive linguistics</a>, the things that belong to a "fuzzy category" exhibit gradations of <a href="/facts/Family_resemblance/Q8QwddBH">family resemblance</a>, and the borders of the category are not clearly defined. 
Through most of the 20th century, the idea of reasoning with fuzzy concepts faced considerable resistance from Western academic elites. They did not want to endorse the use of imprecise concepts in research or argumentation, and they often regarded <a href="/facts/Fuzzy_logic/1PvN4Att">fuzzy logic</a> with suspicion, derision or even hostility. Yet although people might not be aware of it, the use of fuzzy concepts has risen gigantically in all walks of life from the 1970s onward. That is mainly due to advances in electronic engineering, fuzzy mathematics and digital computer programming. The new technology allows very complex inferences about "variations on a theme" to be anticipated and fixed in a program. The <a href="/facts/Perseverance_(rover)/NFoubTKJ">Perseverance</a> Mars <a href="/facts/Mars_rover/6ueforXf">rover</a>, a driverless <a href="/facts/NASA/TIMCV0yV">NASA</a> vehicle used to explore the <a href="/facts/Jezero_crater/jdYzuFPh">Jezero crater</a> on the planet <a href="/facts/Mars/AQGtVvz0">Mars</a>, features fuzzy logic programming that steers it through rough terrain. Similarly, to the North, the Chinese Mars rover <a href="/facts/Zhurong_(rover)/yWh5SXsh">Zhurong</a> used fuzzy logic algorithms to calculate its travel route in <a href="/facts/Utopia_Planitia/ljIwh00X">Utopia Planitia</a> from sensor data. 
New <a href="/facts/Neuro-fuzzy/EY2RTys8">neuro-fuzzy</a> computational methods make it possible for machines to identify, measure, adjust and respond to fine gradations of significance with great precision. It means that practically useful concepts can be coded, sharply defined, and applied to all kinds of tasks, even if ordinarily these concepts are never exactly defined. Nowadays engineers, statisticians and programmers often represent fuzzy concepts mathematically, using fuzzy logic, fuzzy values, fuzzy variables and fuzzy sets (see also <a href="/facts/Fuzzy_set_theory/BGWudHJq">fuzzy set theory</a>). Fuzzy logic is not "woolly thinking", but a "precise logic of imprecision" which reasons with gradations of applicability. It often plays a significant role in <a href="/facts/Artificial_intelligence/lJGauQwX">artificial intelligence</a> programming, for example because it can model human cognitive processes more easily than other methods.

Fuzzy concept open-in-new

Fuzzy concept