Model Based Diagnosis

Model-based diagnosis (MBD) aims to identify the causes of system malfunctions by comparing observed behavior with a pre-existing model. Current research emphasizes efficient algorithms, such as those leveraging MaxSAT solvers or heuristic search, to handle increasingly complex systems and large datasets, including dynamic systems and those with uncertain models. Applications span diverse fields, from software debugging and medical image analysis to industrial process control and system resilience, with a growing focus on integrating MBD with machine learning techniques for improved accuracy and interpretability. The ultimate goal is to develop robust and efficient diagnostic tools that improve system reliability and decision-making across various domains.