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Fuzzy logic is an important concept in medical decision making. Since medical and healthcare data can be subjective or fuzzy, applications in this domain have a great potential to benefit a lot by using fuzzy-logic-based approaches. Fuzzy logic can be used in many different aspects within the medical decision making framework.
In the context of game AI programming, a fuzzy associative matrix helps to develop the rules for non-player characters. [2] Suppose a professional is tasked with writing fuzzy logic rules for a video game monster. In the game being built, entities have two variables: hit points (HP) and firepower (FP):
Nowadays engineers, statisticians and programmers often represent fuzzy concepts mathematically, using fuzzy logic, fuzzy values, fuzzy variables and fuzzy sets [13] (see also fuzzy set theory). Fuzzy logic can play a significant role in artificial intelligence programming, for example because it can model human cognitive processes more easily ...
Lotfi Aliasker Zadeh [5] (/ ˈ z ɑː d eɪ /; Azerbaijani: Lütfi Rəhim oğlu Ələsgərzadə; [6] Persian: لطفی علیعسکرزاده; [2] 4 February 1921 – 6 September 2017) [1] [3] was a mathematician, computer scientist, electrical engineer, artificial intelligence researcher, and professor [7] of computer science at the University of California, Berkeley.
Neuro-fuzzy hybridization is widely termed as fuzzy neural network (FNN) or neuro-fuzzy system (NFS) in the literature. Neuro-fuzzy system (the more popular term is used henceforth) incorporates the human-like reasoning style of fuzzy systems through the use of fuzzy sets and a linguistic model consisting of a set of IF-THEN fuzzy rules.
As explained before, fuzzy logic, one of CI's main principles, consists in measurements and process modelling made for real life's complex processes. [34] It can face incompleteness, and most importantly ignorance of data in a process model, contrarily to Artificial Intelligence, which requires exact knowledge.
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