  The Majority (or Density Classification) Problem in Cellular Automata (CA)
aims to converge a string of cells to a final homogeneous state which reflects
the majority of states present in the initial configuration. The problem is
challenging in CA as individual cells only possess information about their own
and local neighbour states. The problem is an exercise in the propagation and
processing of information within a distributed computational medium. We explore
whether the Majority Problem can be approximated in a similarly simple
distributed computing substrate - a multi-agent model of slime mould. An
initial pattern of discrete voting choices is represented by spatial
arrangement of the agent population, temporarily held in-place by an attractant
stimulus. When this stimulus is removed the model adapts its shape and size,
moving to form a minimal distance connecting line. The final position of this
line is shown, in simple examples, to successfully represent the majority vote
decision, and also accurately reflects the size of the majority. We note
properties, limitations and potential improvements to the approach before
returning full-circle by re-encoding this morphological adaptation approach in
a simple (and more space efficient) 1D CA model.
