Using machine learning techniques for discrete event simulation anlysis

Using machine learning techniques for discrete event simulation analysis

This paper describes an approach to the interpretation of discrete event simulation results using machine learning techniques. The results of two simulators were processed as machine learning problems. In the experiments, the simulation results were interpreted by two attribute-based learning programs Retis and Assistant, and by an Inductive Logic Programming system Markus. Some interesting regularities were thereby automatically discovered.