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.

artificial chemistry, chemical information processing, autonomous robots, genetic programming
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© 2001 Massachusetts Institute of Technology
2001
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