Rule-Based Systems: Theory, Components, and Practical Applications in Real World !!
Abstract A **Rule-Based System (RBS)** is an artificial intelligence system that uses rules as the primary means for decision-making or problem-solving. These systems consist of: 1. **Knowledge Base**: Contains a set of rules that are generally structured in the form of "IF condition THEN action" or "IF condition THEN conclusion." 2. **Inference Engine**: The component that applies the rules to the knowledge base to derive conclusions or make decisions based on input data. It matches the conditions of the rules with the available data and executes the appropriate actions. 3. **User Interface**: Allows interaction between the system and the user, such as inputting data and receiving results. ### Key Features: - **Declarative nature**: Knowledge is represented in the form of rules. - **Transparency**: The reasoning process is typically understandable and explainable, as it follows explicit rules. - **Flexibility**: Easy to update by adding or modify