Abstract:
Knowledge acquisition and knowledge maintenance are problems with any expert system. These problems are exacerbated in domains dealing with temporal data such as the example data sets distributed for AIM-94. Knowledge acquisition for such domains requires information about how features In the data are identified as well as how these features are reasoned about. Ripple Down Rules (RDR) Is a knowledge acquisition methodology which goes some way towards addressing these problems.