Fuzzy Logic
Fuzzy logic is a mathematical framework for handling uncertainty and imprecision in reasoning, extending classical binary logic to allow partial truth values between 0 and 1. It enables systems to model human-like decision-making by using linguistic variables and fuzzy sets, making it particularly useful for control systems and artificial intelligence applications. This approach contrasts with traditional crisp logic, which only deals with absolute true or false states.
Developers should learn fuzzy logic when building systems that require handling ambiguous or noisy data, such as in robotics, automotive control (e.g., anti-lock braking systems), and consumer electronics (e.g., washing machines). It is valuable for applications where human expertise can be encoded into rules, such as in expert systems, medical diagnosis, and natural language processing, to improve adaptability and robustness in uncertain environments.