Evolving control metabolisms for a robot.
This article demonstrates a new method of programming artificial chemistries. It uses the emerging capabilities of the system's dynamics for information-processing purposes. By evolution of metabolisms that act as control programs for a small robot one achieves the adaptation of the internal metabolic pathways as well as the selection of the most relevant available exteroceptors. The underlying artificial chemistry evolves efficient information-processing pathways with most benefit for the desired task, robot navigation. The results show certain relations to such biological systems as motile bacteria.
Ziegler
J
J
Department of Computer Science, University of Dortmund, 44221 Dortmund, Germany. ziegler.banzhaf@ls11.cs.uni-dortmund.de
Banzhaf
W
W
D008660:Metabolism / Q000502:physiology*; D008954:Models, Biological; D008956:Models, Chemical; D012371:Robotics / Q000295:instrumentation* / Q000379:methods