This chapter describes an agile methodology for the development and
evolution of rule-based systems. Intuitive concepts like the system
metaphor, the planning game, and the implementation cycle make its
adoption to arbitrary projects very easy. With the promotion of
continuous techniques such as automated testing and refactoring we cope
with evolutionary aspects of knowledge bases. Further ReadingBaumeister, J.: Advanced Methods for Empirical Testing. FLAIRS'09: Proceedings of the 22th International Florida Artificial Intelligence Research Society Conference. AAAI Press, 2009Baumeister, J.; Menge, M. & Puppe, F.: Visualization Techniques for the Evaluation of Knowledge Systems. FLAIRS'08: Proceedings of the 21th International Florida Artificial Intelligence Research Society Conference. AAAI Press, 2008, S. 329-334 Baumeister, J.; Bregenzer, J. & Puppe, F.: Grey-Box Robustness Testing of Rule Systems. KI'06: Proceedings of the 29th Annual German Conference on Artificial Intelligence, LNAI 4314. Springer, 2006, S. 346-360 Baumeister, J.: Agile Development of Diagnostic Knowledge Systems. IOS Press, AKA, DISKI 284, 2004 Baumeister, J.; Seipel, D. & Puppe, F.: Refactoring Methods for Knowledge Bases. EKAW'04: Engineering Knowledge in the Age of the Semantic Web: 14th International Conference, LNAI 3257. 2004, S. 157-171 About the AuthorsJoachim BaumeisterHomepage: http://www.is.informatik.uni-wuerzburg.de/en/staff/joba Blog: http://ki.informatik.uni-wuerzburg.de/blogs/rokt (ROKT blog) Dietmar Seipel Frank Puppe | ![]() The knowledge modelling environment KnowME ToolsA tool implementing the agile process model is KnowME, the modelling environment of the d3web system. |

