Abstract:
Motivated by the natural phenomenon of living cells self-organizing
into specific shapes and structures, we present
an emergent system that utilizes evolutionary computing
methods for designing and simulating self-aligning and
self-organizing shape primitives. Given the complexity of
the emergent behavior, genetic programming is employed
to control the evolution of our emergent system. The system
has two levels of description. At the macroscopic level, a
user-specified, pre-defined shape is given as input to the
system. The system outputs local interaction rules that direct
morphogenetic primitives (MP) to aggregate into the shape.
At the microscopic level, MPs follow interaction rules based
only on local interactions. All MPs are identical and do not
know the final shape to be formed. The aggregate is then
evaluated at the macroscopic level for its similarity to the
user-defined shape. In this paper, we present (1) an
emergent system that discovers local interaction rules that direct
MPs to form user-defined shapes, (2) the simulation system
that implements these rules and causes MPs to self-align
and self-organize into a user-defined shape, and (3) the
robustness and scalability qualities of the overall approach.
