An Expert System Interpreter for Time Course Data with Refinement in Context

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.