Rule-based systems are a type of artificial intelligence (AI) that use a set of if-then rules to make decisions or perform tasks. These systems are used in a variety of applications, such as expert systems, knowledge-based systems, and decision support systems. In a rule-based system, the rules are typically created by human experts in a specific domain and are used to encode knowledge or expertise about a particular problem. When a new input is presented to the system, it matches the input against the rules and executes the actions specified by the rule that matches the input. Rule-based systems are popular for tasks that involve well-defined and structured problems, as they are easy to understand and interpret by both humans and machines. However, they can be limited in their ability to handle complex or uncertain situations that may not fit neatly into a predefined set of rules. Advances in AI technology, such as machine learning, have helped to address some of these limitations and enhance the capabilities of rule-based systems.