Abstract
One of the main challenges in developmental systems is the design of a method for building complex systems with a structural or computational goal. In previous work, we studied the common properties of several computational architectures consisting of connected computational elements. Their common property of sparsely connected networks, envisages how universal properties and processes can be included in a developmental mapping through an EvoDevo approach. The potentiality of using the same developmental mapping, to develop more than one class of computational architectures was also investigated through Common Developmental Genomes. In this work, the focus is towards development of intra-connected computational architectures, forming a common biological entity - a Hybrid architecture. Also, we explore how common developmental genomes operate under symbiosis and their effect on the evolutionary performance of the partners involved. The results are enlightening gaining a deeper understanding of the capabilities and the limitations of common developmental genomes in these original formations.
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
Kitano, H.: Designing Neural Networks Using Genetic Algorithms with Graph Generation Systems. Complex Systems 4(3), 461–476 (1990)
Miller, J.F., Thomson, P.: A Developmental Method for Growing Graphs and Circuits. In: Tyrrell, A.M., Haddow, P.C., Torresen, J. (eds.) ICES 2003. LNCS, vol. 2606, pp. 93–104. Springer, Heidelberg (2003)
Gordon, T.G.W., Bentley, P.J.: Bias and Scalability in Evolutionary Development. In: Genetic and Evolutionary Computation Conference (GECCO), pp. 83–90 (2005)
Harding, S.L., Miller, J.F., Banzhaf, W.: Self-modifying cartesian genetic programming. In: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation (GECCO), pp. 1021–1028. ACM Press (2007)
Steiner, T., Trommler, J., Brenn, M., Jin, Y., Sendhoff, B.: Global Shape with Morphogen Gradients and Motile Polarized Cells. In: Congress on Evolutionary Computation, pp. 2225–2232. IEEE Press (2009)
Von Neumann, J.: The Theory of Self-reproducing Automata. University of Illinois Press (1966)
Kauffman, S.A., Johnsen, S.: Co-evolution to the edge of chaos: Coupled fitness landscapes, poised states and co-evolutionary avalanches. Artificial Life II, pp. 325–370. Addison-Wesley (1992)
Robert, J.S.: Embryology, Epigenesis and Evolution: Taking Development Seriously. Cambridge Studies in Philosophy and Biology. Cambridge University Press (2004)
Antonakopoulos, K., Tufte, G.: A Common Genetic Representation Capable of Developing Distinct Computational Architectures. In: IEEE Congress on Evolutionary Computation (CEC 2011), pp. 1264–1271 (2011)
Antonakopoulos, K., Tufte, G.: On the Evolvability of Different Computational Architectures using a Common Developmental Genome. In: Rosa, A., Dourado, A., Madani, K., Filipe, J., Kacprzyk, J. (eds.) IJCCI 2012, vol. 2012, pp. 122–129. SciTePress Publishing (2012)
Antonakopoulos, K., Tufte, G.: Is Common Developmental Genome a Panacea Towards More Complex Problems? In: 13th IEEE International Symposium on Computational Intelligence and Informatics (CINTI 2012), pp. 55–61 (2012)
Bull, L., Fogarty, L.C.: Artificial Symbiogenesis. Artificial Life 2(3), 269–292 (1995)
Wilkins, J.: What is a species? Essences and generation. Theory in Biosciences 129(2), 141–148 (2010)
Lindenmayer, A., Prusinkiewicz, P.: Developmental Models of Multicellular Organisms: A Computer Graphics Perspective. In: Langton, C.G. (ed.) Proceedings of ALife, pp. 221–249. Addison-Wesley Publishing (1989)
Stauffer, A., Sipper, M.: Modeling Cellular Development Using L-Systems. In: Sipper, M., Mange, D., Pérez-Uribe, A. (eds.) ICES 1998. LNCS, vol. 1478, pp. 196–205. Springer, Heidelberg (1998)
Antonakopoulos, K., Tufte, G.: Investigation of Developmental Mechanisms in Common Developmental Genomes. In: 7th International ICST Conference on Bio-Inspired Models of Network, Information and Computing Systems (BIONETICS), pp. xxx–xxx. Springer (2012)
Thompson, J.N., Medel, R.: The coevolving web of life. Evolution: Education and Outreach 3(1), 6 (2009)
Momeni, B., Chen, C.C., Hillesland, K.L., Waite, A., Shou, W.: Using artificial systems to explore the ecology and evolution of symbioses. Cellular and Molecular Life Sciences 68(8), 1353–1368 (2011)
Nowak, M., Tarnita, C., Antal, T.: Evolutionary dynamics in structured populations. Philos. Trans. of the Royal Society of London - B Biological Sciences 365(1537), 19–30 (2010)
Bull, L., Alonso-Sanz, R.: On Coupling Random Boolean Networks. Automata 2008: Theory and Applications of Cellular Automata, pp. 292–301. Luniver Press (2008)
Wilkinson, D.M.: At cross purposes. Nature, 412–485 (2001)
Bull, L.: Artificial Symbiogenesis and Differing Reproduction Rates. Artificial Life 16(1), 65–72 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Antonakopoulos, K. (2014). Studying Common Developmental Genomes in Hybrid and Symbiotic Formations. In: Pan, JS., Krömer, P., Snášel, V. (eds) Genetic and Evolutionary Computing. Advances in Intelligent Systems and Computing, vol 238. Springer, Cham. https://doi.org/10.1007/978-3-319-01796-9_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-01796-9_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01795-2
Online ISBN: 978-3-319-01796-9
eBook Packages: EngineeringEngineering (R0)