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Intelligent decision support relies on techniques from a variety of disciplines, including artificial intelligence and database management systems. Most of the existing literature neglects the relationship between these disciplines. By integrating AI and DBMS, Computational Intelligence for Decision Support produces what other texts don't: an explanation of how to use AI and DBMS together to achieve high-level decision making.
Threading relevant disciplines from both science and industry, the author approaches computational intelligence as the science developed for decision support. The...

Effective decision support systems (DSS) are quickly becoming key to businesses gaining a competitive advantage, and the effectiveness of these systems depends on the ability to construct, maintain, and extract information from data warehouses. While many still perceive data warehousing as a subdiscipline of management information systems (MIS), in fact many of its advances have and will continue to come from the computer science arena.Intelligent Data Warehousing presents the state of the art in data warehousing research and practice from a perspective that integrates business applications...

criteria linear and nonlinear programming has proven to be a very useful approach. - Knowledge management for enterprise: These papers address various issues related to the application of knowledge management in corporations using various techniques. A particular emphasis here is on coordination and cooperation. - Risk management: Better knowledge management also requires more advanced techniques for risk management, to identify, control, and minimize the impact of uncertain events, as shown in these papers, using fuzzy set theory and other approaches for better risk management. - Integration...

Intelligent agents are one of the most promising business tools in our information rich world. An intelligent agent consists of a software system capable of performing intelligent tasks within a dynamic and unpredictable environment. They can be characterised by various attributes including: autonomous, adaptive, collaborative, communicative, mobile, and reactive. Many problems are not well defined and the information needed to make decisions is not available. These problems are not easy to solve using conventional computing approaches. Here, the intelligent agent paradigm may play a major...