  Computational models of collective behavior in birds has allowed us to infer
interaction rules directly from experimental data. Using a generic form of
these rules we explore the collective behavior and emergent dynamics of a
simulated swarm. For a wide range of flock size and interaction extent (the
fixed number of neighbors with which an individual will interact) we find that
the computational collective is inherently stable --- individuals are attracted
to one another and will position themselves a preferred distance from their
fixed neighbors within a rigid lattice. Nonetheless, the irregular overall
shape of the flock, coupled with the need for individuals on the boundary to
move towards their neighbors creates a torque which leads the flock to rotate
and then meander. We argue that this "rolling meander" is a very good proxy for
real collective behavior in animal species and yet arises from a simple
homogeneous and deterministic rule for interaction. Rather than then introduce
leaders --- which has already been shown, quite straightforwardly, to drive
collective swarms such as this --- we introduce a small number of "followers".
Each follower is bound to consider a random fixed individual to be among their
neighbors, irrespective of actual metric distance between them. We find that
the introduction of a small number of such followers causes a phase transition
that quickly leads to instability in the flock structure (as no stable
configuration arises) and the previously rigid crystalline interaction among
neighbors now becomes fluid: the distance between neighbors decreases, the
flock ceases to rotate and meanders less.
