Digging for Peace:

Using Machine Learning Methods for

Assessing International Conflict Databases

Robert Trappl, Johannes Furnkranz, Johann Petrak

Austrian Research Institute for Artificial Intelligence

Schottengasse 3, A-1010 Wien

Email: frobert,juffi,johanng@ai.univie.ac.at

Technical Report oefai-tr-96-10

Abstract

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.