Planspiel-Literaturdatenbank des ZMS

Abstract: Artificial Neural Networks make it possible to develop faster modelbased
business games, but in general, they are neither easy to develop nor easy
to understand. This paper presents a highly automated framework for developing
Multi-Layered Networks of Active Neurons for simulation experiments and
model-based business games using self-organizing data mining with the Group
Method of Data Handling. It discusses some of the results from international
research done in Europe, Australia, and most recently at Walla Walla University
in College Place, Washington, USA.

Abstract: Games for decision making have developed into a powerful
tool for corporations. Irrespective of their size, corporations have been
increasingly using these games in order to evaluate and ascertain impactful
business decisions and strategies. Despite their proven added value
to the decision making process, there is still lack of research on whether,
and if so how, these games can be used by researchers and practitioners
to build evidents on systems' behavior, as part of a larger scheme. To
this effect, this paper proposes a framework to determine the different
artifacts of games that should be logged and stored for future use.