Abstract
We have created a model of a hybrid system in which a gene regulatory network (GRN) controls the search for resources (fuel/food and water) necessary to allow an artificial metabolic system (simulated microbial fuel cell) to produce energy. We explore the behaviour of simple animats in a two-dimensional simulated environment requiring minimal cognition. In our system control evolves in a biologically-realistic manner under tight energy constraints. We use a model of GRN in which there is no limit on the size of the network, and the concentration of regulatory substances (transcriptional factors, TFs) change in a continuous fashion. Externally driven concentrations of selected TFs provide the sensory information to the animat, while the concentration of selected internally produced TFs is interpreted as the signal for actuators. We use a genetic algorithm to obtain diverse evolved strategies in ecologically grounded animats with motivational autonomy, even though they lack a dedicated motivational circuit. There are three motivations (or drives) in the system: thirst, hunger, and reproduction. The animats need to search for food and water, but also to perform work. Because the value of such work is arbitrary (in the eye of the beholder), but affects the chances of reproduction, we suggest that the term beauty is more appropriate, and we name the task the Search for Beauty. The results obtained provide a step towards realizing a biologically realistic system with respect to: the way the control is exercised, the way it evolves, and the way the metabolism provides energy.
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Wróbel, B., Joachimczak, M., Montebelli, A., Lowe, R. (2012). The Search for Beauty: Evolution of Minimal Cognition in an Animat Controlled by a Gene Regulatory Network and Powered by a Metabolic System. In: Ziemke, T., Balkenius, C., Hallam, J. (eds) From Animals to Animats 12. SAB 2012. Lecture Notes in Computer Science(), vol 7426. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33093-3_20
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DOI: https://doi.org/10.1007/978-3-642-33093-3_20
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