Deep Interoperation between Diagnostic Distributed Expert Systems
Takahira Yamaguchi and Daiki Kishimoto
When one diagnostic expert system fails in solving problems alone, how can it get information available to improve itself from another similar diagnostic expert system ? This paper presents the interoperation environment to support the process. First, inference primitive structure templates have been presented to share inference structures between two diagnostic expert systems. Next, the cooperation method has been presented, using the difference arising in the context of the correspondence between inference primitives of an originator and those of a recipient. The wrapper with conversion facilities has been also provided, using a common domain ontology developed manually. After designing and implementing such an interoperation environment, the experiment has been done between the following model-based like diagnostic expert systems in real task-domains, a trouble-shooting expert system and an enterprise diagnosis (financial management) expert system. The empirical results have shown us that the former supports the latter in finding a better solution.