This project focuses on the development of artificial intelligence methods for finding short-term patterns in international behavior. Much of the contemporary study of international politics focuses on "events": discrete interactions between nation-states. Events may be as dramatic as the outbreak of war or the signing of a major trade agreement, or as simple as one government congratulating another on its independence day. Individual events can be group into event sequences which describe more complicated behaviors such as conflicts, negotiations or changes in relations. Human observers of international behavior such as journalists, historians and political scientists know that international events follow patterns. A war will almost inevitably be preceded by escalating tensions; a trade agreement will be preceded by months of negotiations. These patterns provide enough regularity in international affairs that expert analysts usually have a good idea of what the likely next events will be, and can also detect unusual changes in behavior. This project will use pattern recognition methods developed in artificial intelligence to detect short-term regularities in contemporary events in the Middle East. The events will be coded from the Foreign Broadcast Information Service (FBIS) reports available from the U.S. Government Printing Office. FBIS reports several hundred events per day: these will be coded into standard categories of events, then the computer programs will look for repeated patterns in those events data. Those patterns can then be used to make predictions much as human analysts use the observed regularities in international behavior to make predictions. The project uses two artificial intelligence methods. One method constructs "partially-ordered event sequences" - - sequences of events which are observed repeatedly because certain events must be preceded by other events (for example, one must have negotiations before one can have a trade agreement). The other method uses "genetic algorithms", which assemble complex event sequences out of simpler sequences using a process resembling evolution. The Principal Investigator has already published several papers employing these methods on historical data; this project will be the first to use them on contemporary data. The project will make three contributions to the understanding of international behavior. First, it will be one of the first efforts to create a computer model of the day-to-day behavior of a contemporary international system, the Middle East. While international relations theory has provided a number of computer models for long-term trends in international politics, relatively little work has been done on short- term behavior. Second, the project will create general tools for finding patterns in political behavior. While these techniques are being developed to study international behavior, the same methods could be used to study any other political, economic or social behavior which can be described using events. Finally, the project will provide some new tools for dealing with large amounts of data generated on a daily basis using relatively inexpensive microcomputer equipment.
