# Intro to Fuzzy Logic

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## What is Fuzzy Logic?

Fuzzy Logic is a approach to computation logic using degrees of truth instead of the standard(boolean) true or false

## Why use Fuzzy Logic?

Fuzzy Logic is conceptually easy to understand; it seems closer to the way our brains work. Fuzzy Logic handles the concept of partial truth;thus, instead of having something as black and white there can be varying shades of grey in between.

## What is a Fuzzy Set?

A fuzzy set is a set that allows elements to be partially in a set unlike a crisp set which an element is either part of a set or not. For example, in a crisp set, a tomato is either a fruit or vegetable it cannot be both while in a fuzzy set a tomato can be bothWhat is a Fuzzy Set?A fuzzy set is a set that allows elements to be partially in a set unlike a crisp set which an element is either part of a set or not. For example, in a crisp set, a tomato is either a fruit or vegetable it cannot be both while in a fuzzy set a tomato can be both.

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## Fuzzy Logic Exercises

### Sorites Paradox Exercise

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Sorite's Paradox is a paradox involving a heap of sand(or some variation) and a paradox arises from the question of when a heap of sand is considered a heap vs a non-heap? The answer in response to this question is fuzzy logic. Fuzzy logic is logic based on degrees of truth(0-1) rather than 0's and 1's (true or false). What this means is that something can be both black and white (grey) instead of being just one of those two choices. So in this exercise, the user is given a choice to decide when a pile of rocks is considered a medium pile and a large pile. From the user's choices, a triangular fuzzy set is drawn to illustrate when a pile is considered small, medium or large

Sorites Paradox Exercise

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### Hertzsprung-Russell Diagram Exercise

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The Hertzsprung-Russell diagram is a diagram showing the relationship of stars based on absolute magnitude and luminosity. In this exercise, this user creates two fuzzy logic sets: one based on absolute magnitude(brightness) and one based on luminosity(temperature/color). After the user creates these sets, the user can create their own fuzzy rulebase. Once the fuzzy sets and rulebase are created, the user can move sliders back and forth to choose a specific brightness and temperature. From these two data points (brightness and temperature), the closest star class will be matched and shown to the user. If nothing matches, the user can go back and add more rules to their rulebase or change their fuzzy sets and try again.

Astronomy Exercise