Expert System

Expert systems aim to mimic human expertise by encoding knowledge into computer programs to solve complex problems. Current research emphasizes improving the accuracy, explainability, and efficiency of these systems, focusing on hybrid approaches that combine rule-based reasoning with machine learning techniques like neural networks, fuzzy logic, and Bayesian networks, often applied within frameworks such as blackboard architectures. These advancements are impacting diverse fields, from optimizing industrial processes and predicting heart disease to supporting legal professionals and improving energy efficiency, demonstrating the broad applicability and growing importance of expert systems in various domains.