An Architecture for a Decision Support System with Incomplete and Domain Incoherent Information Management

N. Malheiro, Z. Vale, and C. Ramos (Portugal)


Temporal Reasoning, Power Systems, NonMonotonic Reasoning, Diagnosis, Event Calculus, Default Logic, Power Systems.


Many of the most common human functions such as temporal and nonmonotonic reasoning have not yet been fully mapped in developed systems, even though some theoretical breakthroughs have already been accomplished. This was mainly due to the inherent computational complexity of the theoretical approaches. In the particular area of fault diagnosis in power systems, however, some systems have been deployed, which tried to solve the problem using methodologies such as production rule based expert systems, neural networks, fuzzy expert systems, etc. SPARSE was one of the developed systems and, in the sequence of its development came the need to cope with incomplete or incorrect information as well as the traditional problems for power systems fault diagnosis based on SCADA information retrieval, namely real-time operation, huge amounts of information, etc. This paper presents an architecture for a decision support system, which can solve the presented problems, using a symbiosis of the Event Calculus and the Default Reasoning rule based system paradigms, insuring soft real time operation with incomplete, incorrect or domain incoherent information handling ability. In the conclusions, the application of this kind of architecture to other problems, namely the agency based electronic commerce is briefly depicted, showing other possibilities for the use of the architecture.

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