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Abstract: Fuzzy logic is a method of reasoning used in artificial intelligence (AI) to mimic human cognition and decision-making. It's used to solve problems with imprecise data or where there's no clear certainty, such as in engineering and natural language processing.    Fuzzy logic uses degrees of truth, represented by real numbers between 0 and 1, instead of the traditional true or false values. This allows it to model concepts with imprecise boundaries or definitions, and to consider all the intermediate possibilities between yes and no.    Here are some examples of how fuzzy logic is used in AI:    Natural language processing Fuzzy logic can be used to process imprecise data, such as in natural language processing technologies.    Temperature control systems Fuzzy logic can be used to regulate and control machine outputs based on multiple inputs.    Classification and regression problems Fuzzy logic is a popular tool fo...

Abstract : Automated reasoning is a computer science field that uses mathematical proof to help determine what a program or system will do. It's a sub-field of artificial intelligence that's also related to theoretical computer science and philosophy.    Here's some more information about automated reasoning:    How it works Automated reasoning uses a reasoning engine to apply inferential logic to a set of hypothesized relationships between system variables. The engine then determines what the individual truths imply about the overall system.    What it's used for Automated reasoning is used to check and verify mathematical proofs, solve problems in engineering, and attack open questions in mathematics and logic.    What it's based on Automated reasoning is based on classical logics and calculi, fuzzy logic, Bayesian inference, and reasoning with maximal entropy.    How it's used in practice AWS uses automated reasoning to re...