System Configuration

System configuration research focuses on optimizing the settings of complex systems to achieve desired performance and functionality. Current efforts concentrate on developing efficient algorithms, such as those based on Bayesian optimization and large language models (LLMs), to automate configuration processes and address challenges like conflicting objectives in multi-objective optimization and variability due to environmental factors. This work is significant for improving the efficiency and reliability of diverse systems, ranging from machine learning models and software applications to robotic systems and communication networks, ultimately leading to more robust and adaptable technologies.