Managing Responsibility and Information Flow in Dynamic Team Decision-Making

We propose a method to allocate decision responsibility and arrange information flow dynamically within a team of decision-makers for command and control. A model of decision making which relates the decision load to decision accuracy is proposed and employed as an atomic building block to create predictive models of team decision making. An optimization problem is then proposed for a given set of forecast decision requirements in which the information flow between the atomic decision-making models is varied so as to maximize an aggregate measure of decision accuracy. A small-scale MATLAB Simulink implementation is presented as well as the outline of current work in which a genetic algorithm is employed to perform the optimization. Preliminary results indicate the technique improves the decisionmaking performance measure. We conclude with a discussion of implementation issues in a larger C2 context.