  The term programmable matter refers to matter which has the ability to change
its physical properties (shape, density, moduli, conductivity, optical
properties, etc.) in a programmable fashion, based upon user input or
autonomous sensing. This has many applications like smart materials, autonomous
monitoring and repair, and minimal invasive surgery. While programmable matter
might have been considered pure science fiction more than two decades ago, in
recent years a large amount of research has been conducted in this field. Often
programmable matter is envisioned as a very large number of small locally
interacting computational particles. We propose the Amoebot model, a new model
which builds upon this vision of programmable matter. Inspired by the behavior
of amoeba, the Amoebot model offers a versatile framework to model
self-organizing particles and facilitates rigorous algorithmic research in the
area of programmable matter. We present an algorithm for the problem of coating
an infinite object under this model, and prove the correctness of the algorithm
and that it is work-optimal.
