User Defined Configuration

User-defined configuration focuses on optimizing system performance and behavior by allowing users to specify parameters and settings tailored to specific needs or contexts. Current research emphasizes automated configuration methods, leveraging machine learning (e.g., XGBoost) and evolutionary algorithms (e.g., SMAC) to find optimal settings across diverse problem instances and applications, including robotics, scheduling, and machine learning model development. This research is significant because it improves efficiency, enhances user experience, and enables the development of more adaptable and robust systems across various domains.