Model-based Diagnosis with the Default-based Diagnosis Engine: Effective Control Strategies that Work in Practice
Oskar Dressler, Peter Struß · 1994
. This paper presents a set of focusing methods for model-based diagnosis systems. They aim at restricting the efforts spent on different computational tasks: the generation of diagnosis candidates, model-based prediction, and dependency recording. Building upon our previous work on exploiting a preference order on component faults in the default-based diagnosis engine (DDE), we formally describe the focusing principles and show their validity in a default logic framework. 1 INTRODUCTION Understanding how complex devices work is difficult enough. Diagnosing them when they don't, is still much harder, because many different faulty behaviors can be exhibited by each system constituent and, in a combinatorial way, by the entire system. Nevertheless, human experts often manage to navigate through this huge space of possibilities quite economically. This economy is essentially grounded on a focusing principle: "Do (or consider) only what appears necessary for the case at hand". Applied to...