Decision making (DM) is an essential component of the problem-solution at many levels - from decisions at international level (e.g. aimed at securing nuclear safety or preventing flood damage), to individual organisations (e.g. increasing productivity or improving urban traffic), systems (e.g. process or robot control, fault detection, medical diagnostics) and to the level of individual human beings following multiple personal aims in their changing environments. Any man-made complex system is composed of DM units called participants. Participants can he machines, groups of humans or their combinations. Attempts to optimise centrally the overall performance of a collection of mutually interacting participants soon reach complexity barrier that allows performance improvements only at unacceptable costs. Use of sophisticated distributed or multiple-participant DM methodologies is then an only viable way towards desirable high efficiency. Excellent particular variants exist that overcome the complexity barrier by exploiting specificity of their application domains. None of them is yet able to serve as a common domain-independent pattern and a real need for theory of multiple-participant DM persists
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