Abstract:
To address how systems of computational agents, working alone, in teams, or with humans, can cooperate to solve problems and advance technology more autonomously than the current generation of remotely controlled unmanned systems, it is increasingly clear that a revolution in computing foundations is necessary (Darpa, 2002). One consequence with current agent systems is that predictions may not be possible (Bankes, 2002). The problem with the traditional computational approach to social processes, such as decision-making, has been attributed to theories based on individual rationality (Lawless & Chandrasekara, 2002; e.g., the «fittest» individual of GA’s, the convergence processes of ANN’s, game theory; an exception might be Robocup in AI,), producing diminishing results even as computational power continues to increase (Darpa, 2002). At the root of the problem is the belief that group decision-making is inferior (see Stroebe & Diehl, 1994, for lab support using toy problems), overlooking the three greatest decision-making groups in the world today: the American stock markets (Insana, 2000), the U.S. Congress (Schlesinger, 1949), and the U.S. Courts (Freer & Perdue, 1996). Making the point, the European Commission is attempting to become an excellent decision-making group (WP, 2001).