Abstract
Evolving large phenotypes remains nowadays a problem due to the combinatorial explosion of the search space. Seeking better scalability and inspired by the development of biological systems several indirect genetic encodings have been proposed. Here two different developmental mechanisms are compared. The first, developed for hardware implementations, relies on simple mechanisms inspired upon gene regulation and cell differentiation. The second, inspired by Cellular Automata, is an Artificial Embryogeny system based on cell-chemistry. This paper analyses the scalability and robustness to phenotypic faults of these two systems, with a direct encoding strategy used for comparison.
Results show that, while for direct encoding scalability is limited by the size of the search space, developmental systems performance appears to be related to the amount of regularity that they can extract from the phenotype. Finally the importance of comparing different genetic encodings is stressed, in particular to evaluate which key characteristics are necessary for better scalability or fault-tolerance. The lack of standard tests or benchmarks is highlighted and some characterisations are proposed.
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
Lehre, P., Haddow, P.C.: Developmental mappings and phenotypic complexity. In: Proceeding of CEC 2003, pp. 62–68 (2003)
Tyrrell, A.M., Sanchez, E., Floreano, D., Tempesti, G., Mange, D., Moreno, J.M., Rosenberg, J., Villa, A.: POEtic Tissue: An Integrated Architecture for Bio- Inspired Hardware. In: Tyrrell, A.M., et al. (eds.) Proc. of the 5th Int. Conf. on Evolvable Systems (ICES 2003), Berlin, pp. 129–140. Springer, Heidelberg (2003)
Roggen, D., Floreano, D., Mattiussi, C.: A Morphogenetic Evolutionary System: Phylogenesis of the POEtic Tissue. In: Tyrrell, A.M., et al. (eds.) Proc. of the 5th Int. Conf. on Evolvable Systems (ICES 2003), Berlin, pp. 153–164. Springer, Heidelberg (2003)
Stanley, K., Miikulainen, R.: A taxonomy for artificial embryogeny. Artificial Life 9(2), 93–130 (2003)
Federici, D.: Using embryonic stages to increase the evolvability of development. To appear in Proceedings of WORLDS workshop at GECCO 2004 (2004)
Miller, J.: Evolving developmental programs for adaptation, morphogenesys, and self-repair. In: Banzhaf, W., Ziegler, J., Christaller, T., Dittrich, P., Kim, J.T. (eds.) ECAL 2003. LNCS (LNAI), vol. 2801, pp. 256–265. Springer, Heidelberg (2003)
Coen, E.: The art of genes. Oxford University Press, New York (1999)
Haddow, P.C., Tufte, G., van Remortel, P.: Shrinking the Genotype: L-systems for EHW? In: Liu, Y., et al. (eds.) Proc. of the 4th Int. Conf. on Evolvable Systems (ICES 2001), Berlin, pp. 128–139. Springer, Heidelberg (2001)
Eggenberger, P.: Cell interactions as a control tool of developmental processes for evolutionary robotics. In: Maes, et al. (eds.) From Animals to Animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior, pp. 440–448. MIT Press-Bradford Books, Cambridge (1996)
Gruau, F.: Automatic definition of modular neural networks. Adaptive Behavior 3, 151–183 (1994)
Kumar, S., Bentley, P.J.: Biologically inspired evolutionary development. In: Tyrrell, A.M., et al. (eds.) Proc. of the 5th Int. Conf. on Evolvable Systems (ICES 2003), Berlin, pp. 57–68. Springer, Heidelberg (2003)
Kitano, H.: Designing neural networks using genetic algorithms with graph generation system. Complex Systems 4(4), 461–476 (1990)
Luke, S., Spector, L.: Evolving graphs and networks with edge encoding: Preliminary report. In: Koza, J.R. (ed.) Late Breaking Papers GP 1996, pp. 117–124 (1996)
Hornby, G.S., Pollack, J.B.: The advantages of generative grammatical encodings for physical design. In: Proceedings of CEC 2001, pp. 600–607 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Roggen, D., Federici, D. (2004). Multi-cellular Development: Is There Scalability and Robustness to Gain?. In: Yao, X., et al. Parallel Problem Solving from Nature - PPSN VIII. PPSN 2004. Lecture Notes in Computer Science, vol 3242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30217-9_40
Download citation
DOI: https://doi.org/10.1007/978-3-540-30217-9_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23092-2
Online ISBN: 978-3-540-30217-9
eBook Packages: Springer Book Archive