INFORMATION-PROCESSING IN KNOWLEDGE-BASED SYSTEMS

Since the pioneering work of Wiener and Shannon in the field of inform ation processing, many developments have focused on the definition of uncertainty measures and their applications to various fields, which c ould be considered as numerical rather than symbolic. During the past twelve years, the researchers in artificial intelligence, who are usua lly preferring symbolic methods, have rediscovered the importance of t hese works and used them to manage the information in knowledge-based systems. We present a brief survey of the different approaches in this framework.