  We consider discrete dynamical systems of "ant-like" agents engaged in a
sequence of pursuits on a graph environment. The agents emerge one by one at
equal time intervals from a source vertex $s$ and pursue each other by greedily
attempting to close the distance to their immediate predecessor, the agent that
emerged just before them from $s$, until they arrive at the destination point
$t$. Such pursuits have been investigated before in the continuous setting and
in discrete time when the underlying environment is a regular grid. In both
these settings the agents' walks provably converge to a shortest path from $s$
to $t$. Furthermore, assuming a certain natural probability distribution over
the move choices of the agents on the grid (in case there are multiple shortest
paths between an agent and its predecessor), the walks converge to the uniform
distribution over all shortest paths from $s$ to $t$.
  We study the evolution of agent walks over a general finite graph environment
$G$. Our model is a natural generalization of the pursuit rule proposed for the
case of the grid. The main results are as follows. We show that "convergence"
to the shortest paths in the sense of previous work extends to all
pseudo-modular graphs (i.e. graphs in which every three pairwise intersecting
disks have a nonempty intersection), and also to environments obtained by
taking graph products, generalizing previous results in two different ways. We
show that convergence to the shortest paths is also obtained by chordal graphs,
and discuss some further positive and negative results for planar graphs. In
the most general case, convergence to the shortest paths is not guaranteed, and
the agents may get stuck on sets of recurrent, non-optimal walks from $s$ to
$t$. However, we show that the limiting distributions of the agents' walks will
always be uniform distributions over some set of walks of equal length.
