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OFAI-TR-96-10 ( 54kB g-zipped PostScript file)

Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases

Robert Trappl, Johannes Fürnkranz, Johann Petrak

In the last decade research in Machine Learning has developed a variety of powerful tools for inductive learning and data analysis. On the other hand, research in International Relations has developed a variety of different conflict databases that are mostly analyzed with classical statistical methods. As these databases are in general of a symbolic nature, they provide an interesting domain for application of Machine Learning algorithms. This paper gives a short overview of available conflict databases and subsequently concentrates on the application of machine learning methods for the analysis and interpretation of such databases.

Citation: Trappl R., Fürnkranz J., Petrak J.: Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases, Proc. of the 12th European Conference on Artificial Intelligence (ECAI-96), 1996.