Fuzzy logic provides an approach to approximate reasoning in which the rules of inference are approximate rather than exact. Fuzzy logic is useful in manipulating information that is incomplete, imprecise, or unreliable. Also called fuzzy set theory, fuzzy logic extends the simple Boolean operators, can express implication, and is used extensively in Artificial Intelligence (AI) programs.

Area of mathematics dealing with Aristotle's “excluded middle.” Yes/no logic pertains only to the world of mathematics. Fuzzy logic pertains to the real world humans live in.

A reasoning paradigm that deals with approximate or imprecise information. Fuzzy logic enables variables to be described (often linguistically) and acted on in terms of their degree of membership in predetermined sets. Control systems in consumer electronics equipment products and other embedded control systems are among the most common applications.

A system which mathematically models complex relationships which are usually handled in a vague manner by language. Under the title of "Fuzzy Logic" falls formal fuzzy logic (a multi-valued form of logic), and fuzzy sets. Fuzzy sets measure the similarity between an object and a group of objects. A member of a fuzzy set can belong to both the set, and its compliment. Fuzzy sets can more closely approximate human reasoning than traditional "crisp" sets. See: Crisp sets.

Fuzzy logic is designed for situations where information is inexact and traditional digital on/off decisions are not possible. It divides data into vague categories such as "hot", "medium" and "cold".

a form of mathematical logic in which truth can assume a continuum of values between 0 and 1

A branch of logic designed specifically to support human reasoning by allowing such linguistic labels as "fairly" and "very" so that statements may be made with varying degrees of certainty and precision. In traditional logic a statement may have one of only two values (true or false). Fuzzy-logic labels and operators allow statements to have multiple values.

A form of artificial intelligence, stored on a computer chip, that enables a camcorder or television to make complex adjustments in focus or picture quality based on ideal models.

A way of dealing with uncertain information and variables that do not permit simple yes/no categorisations (e.g. colour). Can also be used to make decisions where uncertainty occurs (fuzzy control). This is a form of non-Aristotelian logic (see general semantics).

Algorithms that consider a range of acceptable values. It is used to facilitate processing imprecise data.

Processing information that is ambiguous. Fuzzy sets may overlap one another (e.g. something is both sweet and sour). Fuzzy logic uses the operations AND, OR and NOT.

Fuzzy logic is a full text searching technique that will interpret portions of words in a search list so as to find misspelled words or portions of a word that didn't OCR 100% correctly.

In computer science, a form of logic allowing for ambiguous answers to questions that is designed to allow computers to mimic human intelligence.

Logic: Fuzzy logic is an approximate-reasoning logic involving fuzzy set operations that include equality, containment, complementation, intersection and union. It generally is based on min-max or bounded-arithmetic-sum rules for set implication. It is a generalization of conventional multi-valued logic

Fuzzy Logic is an adaptive system that optimises the user`s requirements by means of Artifical Intelligence/Expert System technologies.

Logic without an absolute true or false. Instead, you have gradients of true and false. This is necessary for solving some problems, especially those involving...

An Artificial intelligence method for representing and reasoning with imprecisely specified knowledge, for example defining loose boundaries to distinguish ‘low' from ‘high' values. See also: Qualitative reasoning, Artificial intelligence.

A method used to model linguistic expressions that have non binary truth values. It has been used with PID algorithms in process control, especially where process relationships are nonlinear. (7/96)

One of several alternative calculi for attaching numeric uncertainty values to rules and facts in expert systems. This enables the system to handle imprecise information. As the rules and facts are combined to infer the answer to a problem, the numeric value attached to each one are also combined arithmetically. This gives an uncertainty value to any conclusion drawn from them. Whereas rule-based systems are composed of rules of the form: 'if this set of criteria is satisfied exactly, then take action', fuzzy logic systems' rules resemble the following: 'if this set of criteria is satisfied, in combination, to a given degree, then take action'.

A field of artificial intelligence in which computers analyze logical relationships that are more or less true, in contrast to ordinary logic, where relations are more crisp.

A superset of Boolean logic dealing with the concept of partial truth, in which numbers from 0 to 1 are used as truth values between "completely false" (0) and "completely true" (1).

Mathematical means of dealing with problems that have many solutions

A technique for matching items that are similar. For example if you are using a search engine to find pages containing references to Stephen Thomson using fuzzy logic, it might well return pages that contain Stephen Thompson, Steven Thomson and Steven Thompson as well.

Fuzzy logic is applied to fuzzy sets where membership in a fuzzy set is a probability, not necessarily 0 or 1. Non-fuzzy logic manipulates outcomes that are either true or false. Fuzzy logic needs to be able to manipulate degrees of "maybe" in addition to true and false.

A form of boolean logic that deals with the idea of partial truths. Truth can be considered as a scale between completely true and completely false. Often used in decision making systems dealing with imprecise data.

Fuzzy logic is derived from fuzzy set theory dealing with reasoning that is approximate rather than precisely deduced from classical predicate logic. It can be thought of as the application side of fuzzy set theory dealing with well thought out real world expert values for a complex problem (Klir 1997).

Fuzzy Logic is the name of the debut album by the Super Furry Animals. It was listed in Q Magazine's Best British Albums Ever in July 2004, and in the same magazine's Top 10 Britpop Albums Ever in December 1996. It contains two top 20 hits in 'If You Don't Want Me To Destroy You' and 'Something For The Weekend'; it also contains the singles 'God!