Fuzzy Categories

Fuzzy categories are a way of classifying things when boundaries aren’t clear-cut. Unlike traditional categories with strict yes-or-no criteria, fuzzy categories recognize that some items can partially belong to multiple groups. For example, a person might be "somewhat tall" rather than simply "tall" or "not tall." This approach uses degrees of membership to reflect real-world nuances, making it useful for handling imprecise or ambiguous information. It’s widely applied in fields like artificial intelligence, decision-making, and pattern recognition, where flexibility and ambiguity are inherent.