Of two contradictory approaches to organizations, one builds a plausible story to advance knowledge, and the second resolves the interaction into a physics of uncertainty to make predictions. Both approaches lend themselves to computational agent models, but the former is based on information derived from methodological individualism operating within a stable reality, the latter on interaction uncertainty within a bistable reality. After case studies of decision making for Department of Energy (DOE) Citizen Advisory Boards, we relate the lessons learned to an agent model (EMCAS). We conclude that simple interactions can produce complex stories of organizations, but poorly anchored to reality and of little practical value for decision making. In contrast, with a physics of uncertainty we raise fundamental questions about the value of consensus to instrumental action. We find that by not considering uncertainty in the interaction, the former model instantiates traditional beliefs and cultural values, the latter instrumental action.
|Title of host publication||Computational Economics|
|Subtitle of host publication||A Perspective from Computational Intelligence|
|Number of pages||22|
|Publication status||Published - 1 Dec 2005|