On optimal distributed decision architectures in a hypothesis testing environment

The authors consider the distributed detection problem, in which a set of decision makers (DMs) receive observations of the environment and transmit finite-values messages to other DMs according to prespecified communication protocols. A designated primary DM makes the final decision on one out of two alternative hypothesis. All DMs make decisions, in order to maximize a measure of organizational performance. The problem is to find an architecture for the organization which remains optimal for a variety of operating conditions. It is shown that even for very small organizations this problem is quite complex because the optimal architecture depends on variables external to the team, so that global conclusions on optimal organizational structures cannot be drawn. Suboptimal solutions are considered, and bounds on their performance are obtained