simultaneous information collection predicts. For instance, in a two-level voting system, which has been widely studied in the context of election results [@Davis1973; @Laughlin1975] the final outcome depends heavily upon the distribution of votes in the subgroups, sometimes allowing minority groups to overcome the majority, sometimes exaggerating the power of the majority. It is thus interesting to study the possible effects of such hierarchical systems.

We propose the following model for communication of $n$ participants:

1.  In the beginning there are $n$ agents.

2.  Each turn only $g$ (for our purpose: $2$ or $3$) agents (groups or individuals) share their information according to a chosen model. These agents are then merged into one agent (defined by $s_{model}(s_1,\ldots,s_g)$).

In other words, a group of people who shared information, is treated as a single agent in the next turn. There are two free parameters:

-   The model used to combine members’ parameters into group parameters.

-   How the groups are formed, i.e., the way to determine which agents should interact in given turn.

Let us consider the following ways in which groups can form (see Fig. \[fig:aggregab\] for the diagram of the two first schemes):

-   \[s:ha\] Shallow hierarchy: Each turn $g$ 