connected to the network by creating a new road branching out orthogonally from the nearest edge.

Network initialization is random (see details in \[sec\_extval\]), and the selection of new cells is also random among identical values of $v$. A sensitivity analysis and model exploration is conducted in the next section to determine the relative effect of parameters with respect to these sources of randomness. In any case, growth is halted after a constant amount of time $T$, evaluated from experiments, so that the final structure is neither “unfinished” nor filling out the world (see \[sec\_extval\]). Fig. \[fig\_flowchart\] displays the core ABMS flowchart with feedback interactions between agents.

![The hybrid network/grid model. *Blue arrows*: feedback interactions. *Red arrows*: output evaluation functions.[]{data-label="fig_flowchart"}](lattice){width="0.9\columnwidth"}

![The hybrid network/grid model. *Blue arrows*: feedback interactions. *Red arrows*: output evaluation functions.[]{data-label="fig_flowchart"}](flowchart){width="0.9\columnwidth"}

Evaluation functions
--------------------

Once a structure is generated, its properties need to be quantified so that it can be categorized or compared to other structures for optimization purposes. To this goal, we define various *evaluation functions*, both objective quantification measures and structural fitness values. The measures described in this section take into account all the explicative variables, whose distributions over the grid are emergent properties that cannot 