Embryomorphic Engineering: Emergent Innovation Through Evolutionary Development

  • René Doursat
  • Carlos Sánchez
  • Razvan Dordea
  • David Fourquet
  • Taras Kowaliw
Chapter
Part of the Understanding Complex Systems book series (UCS)

Abstract

Embryomorphic Engineering, a particular instance of Morphogenetic Engineering, takes its inspiration directly from biological development to create new robotic, software or network architectures by decentralized self-assembly of elementary agents. At its core, it combines three key principles of multicellular embryogenesis: chemical gradient diffusion (providing positional information to the agents), gene regulatory networks (triggering their differentiation into types, thus patterning), and cell division or aggregation (creating structural constraints, thus reshaping). This chapter illustrates the potential of Embryomorphic Engineering in different spaces: 2D/3D physical swarms, which can find applications in collective robotics, synthetic biology or nanotechnology; and \(n\)D graph topologies, which can find applications in distributed software and peer-to-peer techno-social networks. In all cases, the specific genotype shared by all the agents makes the phenotype’s complex architecture and function modular, programmable and reproducible.

Notes

Acknowledgments

Since the inception of Embryomorphic Engineering in 2006, R. Doursat’s positions have been funded by the Brain Lab and Department of Computer Science, University of Nevada, Reno; the Complex Systems Institute, Paris Ile-de-France (ISC-PIF), CNRS; and the Research Group in Biomimetics (GEB), Universidad de Málaga, Spain. C.A. Sánchez is a PhD student at GEB since 2011. R. Dordea and D. Fourquet are MSc students by Ecole Polytechnique, Paris. T. Kowaliw is a research scientist at ISC-PIF since 2010, supported by Région Ile-de-France and the French ANR project grant “SynBioTIC” 2010-BLAN-0307-03.

References

  1. 1.
    Abelson, H., Allen, D., Coore, D., Hanson, C., Homsy, G., Nagpal, R., Rauch, E., Sussman, G.J., Weiss, R.: Amorphous computing. Commun. ACM 43(5), 74–82 (2000)CrossRefGoogle Scholar
  2. 2.
    Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Beal, J., Bachrach, J.: Infrastructure for engineered emergence on sensor/actuator networks. IEEE Intell. Syst. 21(2), 10–19 (2006)CrossRefGoogle Scholar
  4. 4.
    Beal, J., Dulman, S., Usbeck, K., Viroli, M., Correll, N.: Organizing the aggregate: languages for spatial computing. Comput. Res. Repos. abs/1202.5509 (2012)Google Scholar
  5. 5.
    Bentley, P., Kumar, S.: Three ways to grow designs: a comparison of embryogenies for an evolutionary design problem. In: Proceedings of the Genetic and Evolutionary Computation Conference, vol. 1, pp. 35–43. Morgan Kaufmann, San Francisco (1999)Google Scholar
  6. 6.
    Callebaut, W., Rasskin-Gutman, D.: Modularity: understanding the development and evolution of natural complex systems. The MIT Press, Cambridge (2005)Google Scholar
  7. 7.
    Carroll, S.B.: Endless Forms Most Beautiful: The New Science of Evo Devo and the Making of the Animal Kingdom. W. W. Norton, New York (2005)Google Scholar
  8. 8.
    Carroll, S.B., Grenier, J.K., Weatherbee, S.D.: From DNA to Diversity: Molecular Genetics and the Evolution of Animal Design. Wiley-Blackwell, Malden (2001)Google Scholar
  9. 9.
    Christensen, A.L., O’Grady, R., Dorigo, M.: Morphology control in a multirobot system. IEEE Robot. Autom. Mag. 14(4), 18–25 (2007)CrossRefGoogle Scholar
  10. 10.
    Coen, E.: The Art of Genes. Oxford University Press, Oxford (2000)Google Scholar
  11. 11.
    Coen, E., Rolland-Lagan, A.G., Matthews, M., Bangham, J.A., Prusinkiewicz, P.: The genetics of geometry. Proc. Natl. Acad. Sci. U. S. A. 101(14), 4728–4735 (2004)CrossRefGoogle Scholar
  12. 12.
    Coore, D.N.: Botanical computing: a developmental approach to generating interconnect topologies on an amorphous computer. Ph.D. thesis, MIT (1999)Google Scholar
  13. 13.
    von Dassow, G., Meir, E., Munro, E.M., Odell, G.M.: The segment polarity network is a robust developmental module. Nature 406, 188–192 (2000)CrossRefGoogle Scholar
  14. 14.
    Dawkins, R.: Climbing Mount Improbable. W.W. Norton& Company, New York (1996)Google Scholar
  15. 15.
    Diaconescu, A., Lalanda, P.: A decentralized, architecture-based framework for self-growing applications. In: Proceedings of the 6th International Conference on Autonomic Computing, pp. 55–56. ACM (2009)Google Scholar
  16. 16.
    Doursat, R.: The growing canavas of biological development: multiscale pattern generation on an expanding lattice of gene regulatory networks. Inter J. Complex Syst. 1809 (2006)Google Scholar
  17. 17.
    Doursat, R.: Organically grown architectures: creating decentralized, autonomous systems by embryomorphic engineering. In: R.P. Würtz (ed.) Organic Computing, Understanding Complex Systems, pp. 167–199. Springer, Heidelberg (2008)Google Scholar
  18. 18.
    Doursat, R.: Programmable architectures that are complex and self-organized: from morphogenesis to engineering. In: Artificial Life XI: Proceedings of the 11th International Conference on the Simulation and Synthesis of Living Systems (Alife XI), pp. 181–188. MIT Press, Cambridge (2008)Google Scholar
  19. 19.
    Doursat, R.: Facilitating evolutionary innovation by developmental modularity and variability. In: Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation (GECCO), pp. 683–690. ACM (2009)Google Scholar
  20. 20.
    Doursat, R., Fourquet, D., Dordea, R., Kowaliw, T.: Morphogenetic engineering by program-limited aggregation. To appear (2013).Google Scholar
  21. 21.
    Doursat, R., Sánchez, C., Fernández, J.D., Kowaliw, T., Vico, F.: Function from structure from development: a dynamical evo-devo model of complex artificial organisms. To appear (2013).Google Scholar
  22. 22.
    Doursat, R., Ulieru, M.: Emergent engineering for the management of complex situations. In: Proceedings of the 2nd International Conference on Autonomic Computing and Communication Systems, vol 14. ICST, Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, 2008Google Scholar
  23. 23.
    Dressler, F.: Self-Organization in Sensor and Actor Networks. Wiley, New York (2007)Google Scholar
  24. 24.
    Edelman, G.M.: Topobiology: An Introduction to Molecular Embryology. Basic Books, New York (1988)Google Scholar
  25. 25.
    Eggenberger, P.: Evolving morphologies of simulated 3d organisms based on differential gene expression. In: Proceedings of the Fourth European Conference on, Artificial Life, pp. 205–213, 1997Google Scholar
  26. 26.
    Floreano, D., Mattiussi, C.: Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies. The MIT Press, Cambridge (2008)Google Scholar
  27. 27.
    Fruchterman, T.M.J., Reingold, E.M.: Graph drawing by force-directed placement. Softw. Pract. Exp. 21(11), 1129–1164 (1991)Google Scholar
  28. 28.
    Gierer, A., Meinhardt, H.: A theory of biological pattern formation. Biol. Cybern. 12(1), 30–39 (1972)Google Scholar
  29. 29.
    Goldstein, S.C., Campbell, J.D., Mowry, T.C.: Programmable matter. Computer 38(6), 99–101 (2005)CrossRefGoogle Scholar
  30. 30.
    Goodwin, B.C.: How the leopard changed its spots: the evolution of complexity. Scribner, New York (1994)Google Scholar
  31. 31.
    Grégoire, G., Chaté, H.: Onset of collective and cohesive motion. Phys. Rev. Lett. 92(2), 025702–025704 (2004)Google Scholar
  32. 32.
    Groß, R., Bonani, M., Mondada, F., Dorigo, M.: Autonomous self-assembly in swarm-bots. IEEE Trans. Robot. 22(6), 1115–1130 (2006)CrossRefGoogle Scholar
  33. 33.
    Hofmeyr, S.A., Forrest, S.: Architecture for an artificial immune system. Evol. Comput. 8(4), 443–473 (2000)CrossRefGoogle Scholar
  34. 34.
    Hogeweg, P.: Evolving mechanisms of morphogenesis: on the interplay between differential adhesion and cell differentiation. J. Theor. Biol. 203(4), 317–333 (2000)CrossRefGoogle Scholar
  35. 35.
    Hornby, G.S., Pollack, J.B.: Creating high-level components with a generative representation for body-brain evolution. Artif. Life 8(3), 223–246 (2002)CrossRefGoogle Scholar
  36. 36.
    Joachimczak, M., Kowaliw, T., Doursat, R., Wrobel, B.: Brainless bodies: controlling the development and behavior of multicellular animats by gene regulation and diffusive signals. In: Artificial Life 13: Proceedings of the Thirteenth International Conference on the Simulation and Synthesis of Living Systems, pp. 349–356, 2012Google Scholar
  37. 37.
    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 Eleventh International Conference on the Simulation and Synthesis of Living Systems, pp. 297–304, 2008Google Scholar
  38. 38.
    Kauffman, S.A.: The Origins of Order: Self Organization and Selection in Evolution. Oxford University Press, Oxford (1993)Google Scholar
  39. 39.
    Kauffman, S.A.: Reinventing the Sacred: A New View of Science, Reason, and Religion. Basic Books, New York (2008)Google Scholar
  40. 40.
    Kirschner, M.W., Gerhart, J.C.: The Plausibility of Life: Resolving Darwin’s Dilemma. Yale University Press, New Haven (2005)Google Scholar
  41. 41.
    Komosinski, M., Rotaru-Varga, A.: Comparison of different genotype encodings for simulated three-dimensional agents. Artif. Life 7(4), 395–418 (2001)CrossRefGoogle Scholar
  42. 42.
    Kondo, S., Asai, R.: A reaction-diffusion wave on the skin of the marine angelfish pomacanthus. Nature 376, 765–768 (1995)CrossRefGoogle Scholar
  43. 43.
    Lipson, H., Pollack, J.B.: Automatic design and manufacture of robotic lifeforms. Nature 406(6799), 974–978 (2000)CrossRefGoogle Scholar
  44. 44.
    Marée, A.F.M., Hogeweg, P.: How amoeboids self-organize into a fruiting body: multicellular coordination in dictyostelium discoideum. Proc. Natl. Acad. Sci. U. S. A. 98(7), 3879–3883 (2001)CrossRefGoogle Scholar
  45. 45.
    Meinhardt, H.: The Algorithmic Beauty of Sea Shells. Springer, Berlin (2003)Google Scholar
  46. 46.
    Miller, J.F., Banzhaf, W.: Evolving the program for a cell: from french flags to boolean circuits. In: On Growth, Form and Computers, pp. 278–301, 2003Google Scholar
  47. 47.
    Mjolsness, E., Sharp, D.H., Reinitz, J.: A connectionist model of development. J. Theor. Biol. 152(4), 429–453 (1991)CrossRefGoogle Scholar
  48. 48.
    Müller, G.B., Newman, S.A.: Origination of Organismal Form: Beyond the Gene in Developmental and Evolutionary Biology. The MIT Press, Cambridge (2003)Google Scholar
  49. 49.
    Nagpal, R.: Programmable self-assembly using biologically-inspired multiagent control. In: Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems: Part 1, pp. 418–425. ACM (2002)Google Scholar
  50. 50.
    Nijhout, H.F.: A comprehensive model for colour pattern formation in butterflies. Proc. Royal Soc. Lond. B Biol. Sci. 239, 81–113 (1990)Google Scholar
  51. 51.
    Nilsson, D.E., Pelger, S.: A pessimistic estimate of the time required for an eye to evolve. Proc. Royal Soc. Lond. Ser. B Biol. Sci. 256(1345), 53–58 (1994)CrossRefGoogle Scholar
  52. 52.
    Prusinkiewicz, P., Lindenmayer, A.: The Algorithmic Beauty of Plants. Springer, New York (1990)Google Scholar
  53. 53.
    Salazar-Ciudad, I., Garcia-Fernández, J., Solé, R.: Gene networks capable of pattern formation: from induction to reaction-diffusion. J. Theor. Biol. 205(4), 587–603 (2000)CrossRefGoogle Scholar
  54. 54.
    Salazar-Ciudad, I., Jernvall, J.: A gene network model accounting for development and evolution of mammalian teeth. Proc. Natl. Acad. Sci. U. S. A. 99, 8116–8120 (2002)Google Scholar
  55. 55.
    Sayama, H.: Decentralized control and interactive design methods for large-scale heterogeneous self-organizing swarms. In: Proceedings of the 9th European Conference on Advances in Artificial Life, pp. 675–684. Springer (2007)Google Scholar
  56. 56.
    Sayama, H.: Swarm chemistry. Artif. Life 15(1), 105–114 (2009)CrossRefGoogle Scholar
  57. 57.
    Sayama, H.: Seeking open-ended evolution in swarm chemistry. In: Artificial Life (ALIFE), 2011 IEEE Symposium on, pp. 186–193. IEEE (2011)Google Scholar
  58. 58.
    Schlosser, G., Wagner, G.P.: Modularity in Development and Evolution. University of Chicago Press, Chicago (2004)Google Scholar
  59. 59.
    Schramm, L., Jin, Y., Sendhoff, B.: Emerged coupling of motor control and morphological development in evolution of multi-cellular animats. In: Advances in Artificial Life. Darwin Meets von Neumann, pp. 27–34, 2011Google Scholar
  60. 60.
    Shapiro, B.E., Levchenko, A., Meyerowitz, E.M., Wold, B.J., Mjolsness, E.D.: Cellerator: extending a computer algebra system to include biochemical arrows for signal transduction simulations. Bioinformatics 19(5), 677–678 (2003)CrossRefGoogle Scholar
  61. 61.
    Siero, P.L.J., Rozenberg, G., Lindenmayer, A.: Cell division patterns: syntactical description and implementation. Comput. Graph. Image Process. 18(4), 329–346 (1982)CrossRefGoogle Scholar
  62. 62.
    Stanley, K.O., Miikkulainen, R.: A taxonomy for artificial embryogeny. Artif. Life 9(2), 93–130 (2003)CrossRefGoogle Scholar
  63. 63.
    Turing, A.M.: The chemical basis of morphogenesis. Philos. Trans. Royal Soc. Lond. Ser. B Biol. Sci. 237, 37–72 (1952)CrossRefGoogle Scholar
  64. 64.
    Ulieru, M., Doursat, R.: Emergent engineering: a radical paradigm shift. Int. J. Auton. Adapt. Commun. Syst. 4(1), 39–60 (2011)CrossRefGoogle Scholar
  65. 65.
    Ulieru, M., Unland, R.: Emergent e-logistics infrastructure for timely emergency response management. In: G. Di Marzo Serugendo et al. (eds.) Engineering Self-Organising Systems: Nature Inspired Approaches to Software Engineering, pp. 139–156. Springer, Berlin (2004)Google Scholar
  66. 66.
    Vicsek, T., Czirók, A., Ben-Jacob, E., Cohen, I., Shochet, O.: Novel type of phase transition in a system of self-driven particles. Phys. Rev. Lett. 75(6), 1226–1229 (1995)CrossRefGoogle Scholar
  67. 67.
    Watson, R.A., Pollack, J.B.: Modular interdependency in complex dynamical systems. Artif. Life 11(4), 445–457 (2005)CrossRefGoogle Scholar
  68. 68.
    Webster, G., Goodwin, B.C.: Form and Transformation: Generative and Relational Principles in Biology. Cambridge University Press, Cambridge (1996)Google Scholar
  69. 69.
    Whitesides, G.M., Grzybowski, B.: Self-assembly at all scales. Science 295, 2418–2421 (2002)CrossRefGoogle Scholar
  70. 70.
    Winfield, A., Harper, C., Nembrini, J.: Towards dependable swarms and a new discipline of swarm engineering. In: Swarm Robotics, pp. 126–142, 2005Google Scholar
  71. 71.
    Wolpert, L.: Positional information and the spatial pattern of cellular differentiation. J. Theor. Biol. 25(1), 1–47 (1969)CrossRefGoogle Scholar
  72. 72.
    Wolpert, L., Beddington, R., Jessell, T., Lawrence, P., Meyerowitz, E., Smith, J.: Principles of Development, vol. 3. Oxford University Press, Oxford (2002)Google Scholar
  73. 73.
    Young, D.A.: A local activator-inhibitor model of vertebrate skin patterns. Math. Biosci. 72(1), 51–58 (1984)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • René Doursat
    • 3
    • 1
  • Carlos Sánchez
    • 2
  • Razvan Dordea
    • 3
  • David Fourquet
    • 3
  • Taras Kowaliw
    • 1
  1. 1.Complex Systems Institute Paris Ile-de-France (ISC-PIF)CNRS and Ecole PolytechniqueParisFrance
  2. 2.Research Group in Biomimetics (GEB)Universidad de MálagaMalagaSpain
  3. 3.Erasmus Mundus Masters in Complex Systems Science (EMMCS)Ecole PolytechniquePalaiseauFrance

Personalised recommendations