Media and Mathematics of Dynamic Networks
This article gives a media-historical overview of several seminal applications of Neighborhood Technologies, (1) in Cellular Automata (CA), (2) in Swarm Intelligence (SI), and (3) in Agent-based Modeling (ABM). It does by no way attempt to be exhaustive, but rather highlights some initial and seminal media-technological contributions towards a mindset which bears neighborhood principles in its core. The text thus centers around media technologies which are based upon the phenomenon that the specific topological settings in local neighborhoods give rise to interesting emergent global patterns which develop dynamically over time and which yield novel ways of generating problem solutions: Autonomy, emergence, and distributed functioning replace preprogramming, control, and centralization. Neighborhood Technologies thus can be understood on two levels: First, as specific spatial structures which initiate non-linear processes over time and whose results often cannot be determined in advance. As an effect, they provide media interfaces which visualize the interplay between local neighborhood interactions and global effects, e.g. in Cellular Automata (CA) where the spatial layout of the media technology enables dynamic processes and at the same time visualizes them as computer graphics. And secondly, they can be perceived as engines of transdisciplinary thinking, bridging fields like mathematical modeling, computer simulation and engineering. Neighborhood Technologies moderate between disciplines e.g. by implementing findings from biology in swarm-intelligent robot collectives whose behavior then is re-applied as an experimental setting for (con-)testing supposed biological factors of collective motion in animal swarms. The central thesis of this article is that Neighborhood Technologies by way of their foundation in neighborhood interaction make the notion of space utterly dynamic and transformable, and always intriguingly connected to functions of time. By their dynamical collective formation, Neighborhood Technologies provide decisive information about complex real-world phenomena.