Multi-human decisionmaking: A control theoretic approach

The distributed nature of human decisionmaking tasks within an organization--civilian as well as military--interacts strongly with the information structure inherent to that organization. Very often these tasks are too complex to be performed by only a single decisionmaker, due to the inherent human limitations of memory, restricted planning horizon, information processing capacity, and mental workload demands. Thus, the functions that make-up any organizational structure are characterized by the interconnections of multiple tasks performed by several humans. In various man machine systems, communications are of crucial importance to each local operator´s performance, as well as to the overall team performance. A strong relationship exists among 1) the degree of interdependence of the subsystems, 2) the communications, information and control sharing requirements, and 3) performance. In this paper, several different theories that have been proposed for studying human team performance are overviewed and their limitations are identified. On the one hand, the existing distributed decisionmaking and control theories do not take into account the inherent human operator limitations. On the other hand, the state of the art models for human decisionmaking deal mainly with the case of a single operator. Thus, there is a potential to fuse both areas of distributed decisionmaking and man machine systems into a single theory which can serve the purpose of analyzing multihuman decisionmaking processes. An attempt to set the bases of such a theory is made for simple human teams with different information structures. The need for the presence of a coordinator, one level of hierarchy above the other decisionmakers is also examined. These studies, together with the normative-descriptive Dynamic Decision Model (DDM) previously developed and validated for a single operator, will form the framework of future experimental designs involving two or more humans making decisions in a mult- -task environment.