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.

[1]  Andreas Flache,et al.  Tools and techniques for social science simulation , 2000 .

[2]  Joseph Y. Halpern,et al.  Causes and Explanations: A Structural-Model Approach. Part II: Explanations , 2001, The British Journal for the Philosophy of Science.

[3]  Jack P. C. Kleijnen,et al.  State-of-the-Art Review: A User's Guide to the Brave New World of Designing Simulation Experiments , 2005, INFORMS J. Comput..

[4]  Bernd Schmidt.  Modelling of Human Behaviour The PECS Reference Model , 2002 .

[5]  J. Pearl.  Causality: Models, Reasoning and Inference , 2000 .

[6]  Christoph Urban,et al.  PECS: A Reference Model for the Simulation of Multi-Agent Systems , 1997, Tools and Techniques for Social Science Simulation.

[7]  Jack P. C. Kleijnen,et al.  A User's Guide to the Brave New World of Designing Simulation Experiments. State-of-the-Art Review , 2005 .

[8]  L. Hluchy,et al.  Graph-based analysis of data from human behaviour simulations , 2012, 2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI).

[9]  Eugene Charniak,et al.  Bayesian Networks without Tears , 1991, AI Mag..

[10]  Bibb Latané,et al.  Dynamic Social Impact , 1996 .

[11]  B. Latané.  Dynamic Social Impact: The Creation of Culture by Communication. , 1996 .

[12]  Judea Pearl,et al.  Fusion, Propagation, and Structuring in Belief Networks , 1986, Artif. Intell..

[13]  Marcel Kvassay,et al.  Towards More Realistic Human Behaviour Simulation: Modelling Concept, Deriving Ontology and Semantic Framework , 2012 .

[14]  Joseph Y. Halpern,et al.  Causes and Explanations: A Structural-Model Approach. Part I: Causes , 2000, The British Journal for the Philosophy of Science.

[15]  Zoubin Ghahramani,et al.  Learning Dynamic Bayesian Networks , 1997, Summer School on Neural Networks.