Computing context-dependent temporal diagnosis in complex domains

Over the years, many Artificial Intelligence (AI) approaches have dealt with the diagnosis problem and its application in complex environments such as medical domains. Model-Based Reasoning (MBR) is one of the approaches that traditionally have tried to solve this problem thanks to its capacity for modelling and reasoning. The consideration of the temporal dimension in these domains is a challenging topic in MBR, especially if temporal imprecision is taken into account. Unfortunately, despite there being many successful MBR systems, there are still two fundamental problems in their development at the aforementioned domains: (1) the degree of dependency between the model used and the domain; and (2) the reutilization of the systems when the domain changes. First this paper proposes a set of basic requirements for the design of Knowledge-Based Systems that will help to solve the problem of temporal diagnosis for environments of high conceptual complexity. From these principles and throu...

• Type: Journal
• Year: 2008
• Where: ESWA
• Authors: José M. Juárez, Manuel Campos, José Palma, Roque Marín
• Keywords: Diagnosis Problem, ESWA 2006, ESWA 2008, Successful Mbr Systems, Temporal Imprecision