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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ashby, W.R.: Principles of the self-organizing dynamic system. In: Principles of Self-Organization: Transactions of the University of Illinois Symposium, vol. 37, pp. 125–128 (1960)
McFarland, D., Spier, E.: Basic cycles, utility and opportunism in self-sufficient robots. Robot Auton. Syst. 20, 179–190 (1997)
Avila-García, O., Cañamero, L.: Hormonal modulation of perception in motivation-based action selection architectures. In: From Animals to Animats 8: Proceedings of the 8th International Conference on Simulation of Adaptive Behavior, pp. 243–252. MIT Press (2004)
Melhuish, C., Ieropoulos, I., Greenman, J., Horsfield, I.: Energetically autonomous robots: food for thought. Auton. Robot 21 (2006)
Montebelli, A., Lowe, R., Ieropoulos, I., Melhuish, C., Greenman, J., Ziemke, T.: Microbial fuel cell driven behavioral dynamics in robot simulations. In: Artificial Life XII: Proceedings of the 12th International Conference on the Simulation and Synthesis of Living Systems, pp. 749–756. MIT Press (2010)
Lowe, R., Montebelli, A., Ieropoulos, I., Greenman, J., Melhuish, C., Ziemke, T.: Grounding motivation in energy autonomy: A study of artificial metabolism constrained robot dynamics. In: Artificial Life XII: Proceedings of the 12th International Conference on the Simulation and Synthesis of Living Systems, pp. 725–732. MIT Press (2010)
Joachimczak, M., Wróbel, B.: Evolving gene regulatory networks for real time control of foraging behaviours. In: Artificial Life XII: Proceedings of the 12th International Conference on the Simulation and Synthesis of Living Systems, pp. 348–355. MIT Press (2010)
Joachimczak, M., Wróbel, B.: Co-evolution of morphology and control of soft-bodied multicellular animats. In: GECCO 2012: Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation. ACM (in press, 2012)
Joachimczak, M., Wróbel, B.: Evo-devo in silico: a model of a gene network regulating multicellular development in 3D space with artificial physics. In: Artificial Life XI: Proceedings of the 11th International Conference on the Simulation and Synthesis of Living Systems, pp. 297–304. MIT Press (2008)
Joachimczak, M., Wróbel, B.: Evolution of the Morphology and Patterning of Artificial Embryos: Scaling the Tricolour Problem to the Third Dimension. In: Kampis, G., Karsai, I., Szathmáry, E. (eds.) ECAL 2009, Part I. LNCS, vol. 5777, pp. 35–43. Springer, Heidelberg (2011)
Eggenberger Hotz, P.: Evolving morphologies of simulated 3D organisms based on differential gene expression. In: Proceedings of the 4th European Conference on Artificial Life, ECAL 1997, pp. 205–213. MIT Press (1997)
Andersen, T., Newman, R., Otter, T.: Shape homeostasis in virtual embryos. Artif. Life 15, 161–183 (2009)
Schramm, L., Sendhoff, B.: An animat’s cell doctrine. In: Advances in Artificial Life, ECAL 2011: Proceedings of the 11th European Conference on the Synthesis and Simulation of Living Systems, pp. 739–746. MIT Press (2011)
Joachimczak, M., Wróbel, B.: Processing signals with evolving artificial gene regulatory networks. In: Artificial Life XII: Proceedings of the 12th International Conference on the Simulation and Synthesis of Living Systems, pp. 203–210. MIT Press (2010)
Kuo, P.D., Leier, A., Banzhaf, W.: Evolving Dynamics in an Artificial Regulatory Network Model. In: Yao, X., Burke, E.K., Lozano, J.A., Smith, J., Merelo-Guervós, J.J., Bullinaria, J.A., Rowe, J.E., Tiňo, P., Kabán, A., Schwefel, H.-P. (eds.) PPSN 2004. LNCS, vol. 3242, pp. 571–580. Springer, Heidelberg (2004)
Knabe, J.F., Nehaniv, C.L., Schilstra, M.J., Quick, T.: Evolving biological clocks using genetic regulatory networks. In: Artificial Life X: Proceedings of the 10th International Conference on the Simulation and Synthesis of Living Systems, pp. 15–21. MIT Press (2006)
Bentley, P.J.: Adaptive fractal gene regulatory networks for robot control. In: Workshop on Regeneration and Learning in Developmental Systems in the Genetic and Evolutionary Computation Conference (GECCO 2004) (2004)
Taylor, T.: A genetic regulatory network-inspired real-time controller for a group of underwater robots. In: Proceedings of the Eighth Conference on Intelligent Autonomous Systems (IAS-8), pp. 403–412 (2004)
Quick, T., Nehaniv, C.L., Dautenhahn, K., Roberts, G.: Evolving Embodied Genetic Regulatory Network-Driven Control Systems. In: Banzhaf, W., Ziegler, J., Christaller, T., Dittrich, P., Kim, J.T. (eds.) ECAL 2003. LNCS (LNAI), vol. 2801, pp. 266–277. Springer, Heidelberg (2003)
Montebelli, A., Lowe, R., Ziemke, T.: Towards metabolic robotics: insights from modeling embodied cognition in a bio-mechatronic symbiont. Artif. Life (in press, 2012)
Bagorda, A., Parent, C.A.: Eukaryotic chemotaxis at a glance. J. Cell Sci. 121, 2621–2624 (2008)
Beer, R.: Toward the evolution of dynamical neural networks for minimally cognitive behavior. In: From Animals to Animats 4: International Conference on Simulation of Adaptive Behavior, pp. 421–429 (1996)
Saglimbeni, F., Parisi, D.: Input from the External Environment and Input from within the Body. In: Kampis, G., Karsai, I., Szathmáry, E. (eds.) ECAL 2009, Part I. LNCS, vol. 5777, pp. 148–155. Springer, Heidelberg (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-642-33093-3_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33092-6
Online ISBN: 978-3-642-33093-3
eBook Packages: Computer ScienceComputer Science (R0)