Detecting Traac Problems with Ilp

Expert systems for decision support have recently been successfully introduced in road transport management. These systems include knowledge on traac problem detection and alleviation. The paper describes experiments in automated acquisition of knowledge on traac problem detection. The task is to detect road sections where a problem has occured (critical sections) from sensor data. It is necessary to use inductive logic programming (ILP) for this purpose as relational background knowledge on the road network is essential. In this paper, we apply three state-of-the art ILP systems to learn how to detect traac problems and compare their performance to the performance of a propo-sitional learning system on the same problem.