Abstract
A method for evolving a developmental program inside a cell to create multicellular organisms of arbitrary size and characteristics is described. The cell genotype is evolved so that the organism will organize itself into well defined patterns of differentiated cell types (e.g. the French Flag). In addition the cell genotypes are evolved to respond appropriately to environmental signals that cause metamorphosis of the whole organism. A number of experiments are described that show that the organisms exhibit emergent properties of self-repair and adaptation.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Abelson, H., Allen, D., Coore, D., Hanson, C., Homsy, G., Knight Jr., T., Nagpal, R., Rauch, E., Sussman, G.J., Weiss, R.: Amorphous Computing, MIT Tech. report, AI Memo 1665 (1999)
Astor, J.C., Adami, C.: A Development Model for the Evolution of Artificial Neural Networks. Artificial Life 6, 189–218 (2000)
Bentley, P., Kumar, S.: Three ways to grow designs: A comparison of embryogenies for an Evolutionary Design Problem. In: Proceedings of the Congress on Evolutionary Computation, pp. 35–43. IEEE Press, Los Alamitos (1999)
Boers, E.J.W., Kuiper, H.: Biological metaphors and the design of modular neural networks, Masters thesis, Department of Computer Science and Department of Experimental and Theoretical Psychology, Leiden University (1992)
Bongard, J.C., Pfeifer, R.: Repeated Structure and Dissociation of Genotypic and Phenotypic Complexity in Artificial Ontogeny. In: Spector, L., et al. (eds.) Proceedings of the Genetic and Evol. Comput. Conference, pp. 829–836. Morgan-Kaufmann, San Francisco (2001)
Cangelosi, A., Parisi, D., Nolfi, S.: Cell Division and Migration in a ’Genotype’ for Neural Networks, Tech. report PCIA-93, Inst. of Psych., CNR, Rome (1993)
Dellaert, F.: Toward a Biologically Defensible Model of Development, Masters thesis, Dept. of Computer Eng. and Science, Case Western Reserve University (1995)
Eggenberger, P.: Evolving morphologies of simulated 3D organisms based on differential gene expression. In: Proc. Of European Conf. on Artificial Life, pp. 205–213 (1997)
Fleischer, K., Barr, A.H.: A simulation testbed for the study of multicellular development: The multiple mechanisms of morphogenesis. In: Langton, C.G. (ed.) Proceedings of the 3rd Workshop on Artificial Life, pp. 389–416. Addison-Wesley, Reading (1992)
Furusawa, C., Kaneko, K.: Emergence of Multicellular Organisms with Dynamic Differentiation and Spatial Pattern. In: Adami, C., et al. (eds.) Proceedings of the 6th International Conference on Artificial Life. MIT Press, Cambridge (1998)
Gruau, F.: Neural Network Synthesis using Cellular Encoding and the Genetic Algorithm, PhD thesis, Ecole Normale Supérieure de Lyon (1994)
Gruau, F., Whitley, D., Pyeatt, L.: A Comparison between Cellular Encoding and Direct Encoding for Genetic Neural Networks. In: Proc. of the 1st Annual Conference on Genetic Programming, Stanford (1996)
Hogeweg, P.: Evolving Mechanisms of Morphogenesis: on the Interplay between Differential Adhesion and Cell Differentiation. J. Theor. Biol. 203, 317–333 (2000)
Hogeweg, P.: Shapes in the Shadow: Evolutionary Dynamics of Morphogenesis. Artificial Life 6, 85–101 (2000)
Hornby, G.S., Pollack, J.B.: The Advantages of Generative Grammatical Encodings for Physical Design. In: Proceedings of the Congress on Evolutionary Computation, pp. 600–607. IEEE Press, Los Alamitos (2001)
Jacobi, N.: Harnessing Morphogenesis, Cognitive Science Research Paper 423, COGS. University of Sussex (1995)
Kitano, H.: Designing neural networks using genetic algorithms with graph generation system. Complex Systems 4, 461–476 (1990)
Kodjabachian, J., Meyer, J.-A.: Evolution and Development of Neural Controllersfor Locomotion, radient-Following and Obstacle-Avoidance in Artificial Insects. IEEE Transactions on Neural Networks 9, 796–812 (1998)
Koza, J.R.: Genetic Programming: On the programming of computers by means of natural selection. MIT Press, Cambridge (1992); Genetic Programming II: Automatic Discovery of Reusable Subprograms. MIT Press (1994)
Lindenmeyer, A.: Mathematical models for cellular interaction in development, parts I and II. Journal of Theoretical Biology 18, 280–315 (1968)
Miller, J.F., Thomson, P.: Cartesian genetic programming. In: Poli, R., Banzhaf, W., Langdon, W.B., Miller, J., Nordin, P., Fogarty, T.C. (eds.) EuroGP 2000. LNCS, vol. 1802, pp. 121–132. Springer, Heidelberg (2000)
Nolfi, S., Parisi, D.: Growing neural networks, Technical report PCIA-91-15, Institute of Psychology, CNR, Rome (1991)
Siddiqi, A.A., Lucas, S.M.: A comparison of matrix rewriting versus direct encoding for evolving neural networks. In: Proceedings of the 1998 IEEE International Conference on Evolutionary Computation, pp. 392–397. IEEE Press, Los Alamitos (1998)
Sims, K.: Evolving 3D morphology and behaviour by competition, In: Proceedings of Artificial Life IV, pp. 28–39 (1994)
Vassilev, V.K., Miller, J.F.: The advantages of landscape neutrality in digital circuit evolution. In: Miller, J.F., Thompson, A., Thompson, P., Fogarty, T.C. (eds.) ICES 2000. LNCS, vol. 1801, pp. 252–263. Springer, Heidelberg (2000)
Wolpert, L.: Principles of Development. Oxford University Press, Oxford (1998)
Yu, T., Miller, J.: Neutrality and the evolvability of Boolean function landscape. In: Proceedings of the 4th European Conference on Genetic Programming, pp. 204–217. Springer, Heidelberg (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Miller, J.F. (2003). Evolving Developmental Programs for Adaptation, Morphogenesis, and Self-Repair. In: Banzhaf, W., Ziegler, J., Christaller, T., Dittrich, P., Kim, J.T. (eds) Advances in Artificial Life. ECAL 2003. Lecture Notes in Computer Science(), vol 2801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39432-7_28
Download citation
DOI: https://doi.org/10.1007/978-3-540-39432-7_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20057-4
Online ISBN: 978-3-540-39432-7
eBook Packages: Springer Book Archive