Fuzzy Fault Evaluation In Causal DiagnosticReasoning
Pilar Pozos Parra, Antoni Ligęza · WIT transactions on information and communication technologies · 1970
Causal reasoning is a practical support for model-based diagnosis [1]. The paper addresses the issues of extending diagnostic reasoning based on abductive analysis of causal structures. The extension is aimed at admitting fuzzy characterization of faults; binary evaluation (i.e. faulty/correct) is no longer necessary. The degree of faultyness is expressed with use of basic fuzzy notions. This extension uses a uniform model for representing causal behaviour of diagnosed systems: it has the form of an AND/OR/NOT causal graph allowing for specification of causality types reflecting the basic logical operations [3]. The graph can be used to search for potential (possible) diagnoses. Validation of generated diagnoses is performed by propagation of fuzzy faults upwards the graph [3]. A motivational discussion introducing the presented ideas at an intuitionistic level is presented in brief. Finally, possibilities for further extensions and related work are pointed out.