Abstract

In an algorithmic artificial chemistry the objects (molecules) are data and the interactions (reactions) among them are defined by an algorithm. The same object can appear in two forms: (1) as a machine (operator) or (2) as data (operand). Thus, the same object can, on the one hand, process other objects or, on the other hand, it can be processed. This dualism enables to implicitly define a constructive artificial chemistry which exhibits quite complex behavior. Remarkably, even evolutionary behavior emerged in our experiments, without defining any explicit variation operators or fitness-function. In addition to microscopic methods (e.g., monitoring the actions of single molecules) and macroscopic measures (e.g., diversity or complexity) we developed a stepwise mesoscopic analysis method based on classification and dynamic clustering. Knowledge about the system is accumulated by an iterative process in which measuring tools (classificators) extract information which i...

Citations