  In this paper, we identify a radically new viewpoint on the collective
behaviour of groups of intelligent agents. We first develop a highly general
abstract model for the possible future lives that these agents may encounter as
a result of their decisions. In the context of these possible futures, we show
that the causal entropic principle, whereby agents follow behavioural rules
that maximise their entropy over all paths through the future, predicts many of
the observed features of social interactions between individuals in both human
and animal groups. Our results indicate that agents are often able to maximise
their future path entropy by remaining cohesive as a group, and that this
cohesion leads to collectively intelligent outcomes that depend strongly on the
distribution of the number of future paths that are possible. We derive social
interaction rules that are consistent with maximum-entropy group behaviour for
both discrete and continuous decision spaces. Our analysis further predicts
that social interactions are likely to be fundamentally based on Weber's law of
response to proportional stimuli, supporting many studies that find a
neurological basis for this stimulus-response mechanism, and providing a novel
basis for the common assumption of linearly additive 'social forces' in
simulation studies of collective behaviour.
