Self-Organizing Particle Systems
We investigate the capabilities and properties of distributed systems that consist of myriads of simple computational particles. These particle systems are able to self-organize in order to solve their designated tasks without any central control. Self-organizing particle systems have many interesting applications like coating objects for monitoring and repair purposes and forming nano-scale devices for surgery and molecular-scale electronic structures. The notion of programmable matter is tightly interwoven with the term self-organizing particle systems, which has the ability to change its physical properties (shape, density, moduli, conductivity, optical properties, etc.) in a programmable fashion.
We aim to build a theoretical foundation for self-organizing particle systems that allows rigorous algorithmic research. In doing so, we attempt to provide a universal model that is able to capture many underlying assumptions and physical properties of particle systems in general. In our preliminary work we propose the amoebot model which we use to investigate shape formation and coating problems in a simple setting.