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Hybrid Intelligent Decision Support Systems for Risk Analysis and Prediction of Evolving Economic Clusters in Europe

Decision making in a complex, dynamic environment is a very difficult task that requires new techniques of computational intelligence for building adaptive, hybrid intelligent decision support systems (HIDSS). Here, a new approach is proposed based on evolving agents in a dynamic environment. Neural network and rule-based agents are evolved using methods included in a repository for intelligent connectionist based information systems (RICBIS). A case study project on risk analysis of the European Monetary Union (EMU) is carried out and a framework of system is presented along with some preliminary results.