다중 상황공간을 이용한 다중 오류의 고장 진단 = Diagnosing Multiple Faults using Multiple Context Spaces

다국어 초록 (Multilingual Abstract)

Diagnostic problem solving is a major application area of knowledge-based system research. However, most of the current approaches, both heuristic and model-based, are designed to identify single faults, and do not generalize easily to multiple fault diagnosis without exhibiting exponential behavior in the amount of computation required. In this paper, we employ a decomposition approach based on system configuration to generate an efficient algorithm for multiple fault diagnosis. The basic idea of the algorithm is to reduce the inherent combinatorial explosion that occurs in generating multiple faults by partitioning the circuit into groups that correspond to output measurement points. Rules are developed for combining candidates from individual groups, and forming consistent sets of minimal candidates.