Which type of AI Model uses if-then rules to make decisions?

The correct answer is fuzzy logic models, as they are explicitly designed to handle reasoning that is approximate rather than fixed and exact. These models use if-then rules, which allows them to mimic human reasoning more effectively in situations where binary true/false logic may not apply. Fuzzy logic systems take into account the degree of truth as a continuum between 0 and 1, making them well-suited for scenarios where ambiguity and uncertainty are commonly encountered.

Statistical models utilize statistical methods to infer relationships and analyze data, but they do not typically operate through explicit if-then logical structures like fuzzy logic does. Neural networks, on the other hand, are based on interconnected nodes and learn from data through training, without relying on defined rules for decision-making. Linear models use algebraic equations to predict outcomes based on input variables but do not employ the if-then format for logic processing.