Information transmission in collectively moving agents.

Information may be any internal degree of freedom, such as
disease status, knowledge, etc.. In fact the collectively moving
agents can be foraging territorial animals or surveying robots
searching for some targets.

Encounter and coverage statistics are essential to understand
when information is optimal (robots) or when it should be
minimized (disease spread)

What is the role of movement statistics, e.g. drift or correlated
random walker, of the individuals on the efficiency of
information transfer? And what happens if the space that agents
share is not the same, eg. territorial robots and animals with
partially overlapping territories?

We will use the new analytic results on random walk propagators
confined in finite domains to tackle the pairwise interaction
scenarios. And from those results it will be possible to
interpret the outcome of the collective movement models, either
animals or robots.