On the relationship between decision uncertainty and interaction level: a new model for team optimization

The purpose of this paper is to investigate the effects of uncertainty on interaction in the framework of team optimization. An optimization problem with multiple decision makers is considered, where there is uncertainty in the decisions made by the other decision makers. For this novel problem framework, the level of interaction and the level of uncertainty are defined, and the relationship between these two levels is derived. For a broad class of problems, it is shown that the optimal level of interaction decreases as the level of uncertainty increases. In some cases, when the uncertainty increases, the optimal level of interaction tends to zero. The optimization problem then becomes decoupled, making it less computationally intensive. The theoretical results are illustrated by an example drawn from Internet routing. The paper concludes with a short summary of the results and comments on future research directions