Towards causal analysis of data from human behaviour simulations

In this article, which is a report of work in progress, we explore the principles of Bayesian causal analysis broadly along the lines formulated by Judea Pearl and other researchers. We apply these principles in the context of human behaviour modelling and aim at developing intelligent data analysis methods for large scale data sets, more specifically for logs from realistic simulations of human behaviour and data farming experiments in the context of the EDA project A-0938-RT-GC EUSAS.