Decision making becomes more complicated and difficult in today's rapid changed decision environment than ever before. Decision makers often require increasing technical support to high quality decisions in a timely manner. Decision support systems (DSS), as a kind of interactive computer-based information systems, help decision makers utilize data and models to solve mostly semi-structured or un-structured decision problems in practice. Intelligent DSS, along with knowledge-based decision analysis models and methods, incorporate well databases, model bases and intellectual resources of individuals or groups to improve the quality of complex decisions. In the recent years, multi-criteria DSS, group DSS, and web-based customer recommender systems have had unimaginable developments and improvements in dealing with complex, uncertain, and un-structured decision problems under the support of computational intelligent technologies.
A closely related area of DSS is warning systems (WS). It is a means of generating maximally reliable and accurate information on a possible threat or an impending emergency, facilitating good decisions through risk analysis and prediction. There are growing desires to improve effectiveness of warning generation and warning reliability and to make intelligent decision analysis to achieve higher technical levels of WS in complex, unintended and dynamic environments. Intelligent techniques such as machine learningbased prediction methods can basically support establishing a technical process of uncertain multi-source information fusion and warning deriving. They can also support developing humaninvolved decision models for risk assessments, reasoning-based warning decisions, emergency management systems, and various warning systems.
This special issue offers an updated overview of the research field in line with decision support and warning systems integrated with knowledge based learning and computational intelligent techniques. It was generated from the eighth International FLINS Conference on Computational Intelligence in Decision and Control, Madrid, Spain, September 21-24, 2008 (http://www.mat.ucm.es/ congresos/flins2008/) by selecting nine relevant papers in the scope of the special issue. This very small set of selections out of over 200 papers in the FLINS2008 proceedings presents recent developments of methodologies, techniques and applications in intelligent decision support and warning systems from multiple aspects. The special issue covers ranging from intelligent decision support systems (papers 1-5), intelligent risk analysis and warning systems (papers 6-8), to knowledge-based decision intelligence methodologies (paper 9).
The first paper on a fuzzy information axiom-based group DSS by Cebi and Kahraman shows how fuzzy logic-based learning techniques can play an effective role to understand time-varying/ inconsistent and user-dependent characteristics of human bio-signal in a decision process. A probabilistic fuzzy rule-based life-long