Rule-Based Decision Making
Rule-based decision making is a methodology where decisions are made by applying a predefined set of logical rules or conditions to input data. It involves creating explicit if-then statements or decision trees that map specific conditions to corresponding actions or outcomes. This approach is commonly used in systems where decisions need to be transparent, consistent, and based on clear criteria, such as in business processes, expert systems, or automated workflows.
Developers should learn rule-based decision making when building systems that require deterministic, repeatable decisions based on explicit logic, such as in fraud detection, eligibility screening, or automated customer support. It is particularly useful in scenarios where decision transparency and auditability are critical, as rules can be easily documented and understood by non-technical stakeholders. This methodology also serves as a foundation for more advanced AI techniques, making it a valuable skill for transitioning into machine learning or knowledge-based systems.