Automatic Configuration

Automatic configuration aims to optimize the settings of complex systems, such as databases, optimization solvers, and machine learning models, automatically improving performance and efficiency. Current research focuses on leveraging machine learning, particularly reinforcement learning and Bayesian optimization, often within frameworks incorporating explainability and efficient search strategies like tree-based models or mathematical programming formulations. This field is significant because it addresses the growing challenge of managing increasingly intricate systems, offering substantial benefits across diverse applications from database administration and network optimization to accelerating the development of AI models.