What Is Fuzzy Logic?

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Fuzzy logic is a way of thinking about and dealing with the world that's more like how humans think. Do you know? We don't have binary logic as computers do. It's all about gradients, shades of gray, and ranges of values. Two-valued logic—the kind computers use—can't handle that complexity. But fuzzy logic can! Fuzzy logic employs many-valued logic rather than binary (two-valued) to perform logical operations. While binary logic uses values of 0 and 1 to represent false and true (respectively), fuzzy logic uses values between 0 and 1 to express the level of veracity (much or minor). Fuzzy logic may be used in various fields, including control systems, neural networks, and artificial intelligence. Fuzzy logic is a form of reasoning that works with vague statements. In traditional logic, all statements are either true or false. Fuzzy logic allows for statements that are neither entirely true nor completely false. This approach can be helpful in many fields, including control systems and AI. Control systems use fuzzy logic to decide how much energy or water should flow through a system at any given time. Fuzzy logic can also be used in neural networks, which are computer models that mimic how human brains process information. Fuzzy logic is a powerful tool for understanding how humans think. Let's say you want to know what humans think about fat and thin people. You might ask five people to rank how lean or fat they believe each person is but, the results would be all over the map! Some might rank one person as "very thin," while others are "very fat." If you've ever tried to lose weight, you know that your body doesn't always define "thin" and "fat" in the same way. It's easy to see why: everyone has a different idea of what those terms mean. And once you start talking about other people, it gets even more complicated—if someone looks thin to me but not my friend, does that mean they're obese? Or am I just being judgmental? But there's hope! Fuzzy logic can help us understand what our brains are doing when they make these types of judgments—and how we can get them to make better decisions in the future.

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