What is the mathematical method of handling imprecise or subjective information called?

The mathematical method of handling imprecise or subjective information is called fuzzy logic. This approach is particularly useful in situations where traditional binary logic (true or false) cannot adequately capture the nuances of real-world scenarios, where information may be uncertain or vague. Fuzzy logic allows for reasoning that is approximate rather than fixed and exact, enabling systems to respond more effectively to changing and ambiguous conditions.

Fuzzy logic assigns degrees of truth to the values rather than a simple true/false dichotomy. For instance, in a fuzzy logic system, a statement like "The room is warm" can have a truth value anywhere between 0 and 1, representing levels of warmth rather than a definitive answer. This flexibility makes fuzzy logic especially valuable in fields such as control systems, artificial intelligence, and decision-making processes, where human-like reasoning is beneficial.

In contrast, the other options refer to different concepts: mutation generally relates to changes in genetic material, augmented reality involves enhancing real-world environments with computer-generated elements, and data mining focuses on extracting patterns from large datasets. None of these directly address the handling of imprecise or subjective information as effectively as fuzzy logic does.