  We consider programmable matter consisting of simple computational elements,
called particles, that can establish and release bonds and can actively move in
a self-organized way, and we investigate the feasibility of solving fundamental
problems relevant for programmable matter. As a suitable model for such
self-organizing particle systems, we will use a generalization of the geometric
amoebot model first proposed in SPAA 2014. Based on the geometric model, we
present efficient local-control algorithms for leader election and line
formation requiring only particles with constant size memory, and we also
discuss the limitations of solving these problems within the general amoebot
model.
