Morphogenetic Engineering: Reconciling Self-Organization and Architecture

Chapter
Part of the Understanding Complex Systems book series (UCS)

Abstract

Generally, phenomena of spontaneous pattern formation are random and repetitive, whereas elaborate devices are the deterministic product of human design. Yet, biological organisms and collective insect constructions are exceptional examples of complex systems that are both architectured and self-organized. Can we understand their precise self-formation capabilities and integrate them with technological planning? Can physical systems be endowed with information, or informational systems be embedded in physics, to create autonomous morphologies and functions? This book is the first initiative of its kind toward establishing a new field of research, Morphogenetic Engineering, to explore the modeling and implementation of “self-architecturing” systems. Particular emphasis is set on the programmability and computational abilities of self-organization, properties that are often underappreciated in complex systems science—while, conversely, the benefits of self-organization are often underappreciated in engineering methodologies.

References

  1. 1.
    Abelson, H., Allen, D., Coore, D., Hanson, C., Homsy, G., Knight Jr, T.F., Nagpal, R., Rauch, E., Sussman, G.J., Weiss, R.: Amorphous computing. Commun. ACM 43(5), 74–82 (2000)Google Scholar
  2. 2.
    Ball, P.: The Self-Made Tapestry. Oxford University Press, Oxford (1999)Google Scholar
  3. 3.
    Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Barrat, A., Barthélemy, M., Vespignani, A.: Dynamical Processes on Complex Networks. Cambridge University Press, New York (2008)Google Scholar
  5. 5.
    Beal, J., Bachrach, J.: Infrastructure for engineered emergence on sensor/actuator networks. IEEE Intell. Syst. 21(2), 10–19 (2006)CrossRefGoogle Scholar
  6. 6.
    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
  7. 7.
    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 (1999)Google Scholar
  8. 8.
    Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New. York (1999)Google Scholar
  9. 9.
    Brooks, R.: A robust layered control system for a mobile robot. IEEE J. Robot. Autom. 2(1), 14–23 (1986)CrossRefGoogle Scholar
  10. 10.
    Bullock, S., Ladley, D., Kerby, M.: Wasps, termites and waspmites: distinguishing competence from performance in collective construction. Artif. Life 18(3), 267–290 (2012)Google Scholar
  11. 11.
    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
  12. 12.
    Coen, E.: The Art of Genes. Oxford University Press, Oxford (2000)Google Scholar
  13. 13.
    Coore, D.N.: Botanical computing: a developmental approach to generating interconnect topologies on an amorphous computer. Ph.D. thesis, MIT (1999)Google Scholar
  14. 14.
    Dorigo, M., Stützle, T.: Ant Colony Optimization. The MIT Press, Cambridge (2004)Google Scholar
  15. 15.
    Doursat, R.: Organically grown architectures: creating decentralized, autonomous systems by embryomorphic engineering. In: Würtz, R.P. (ed.) Organic Computing, Understanding Complex Systems, pp. 167–199. Springer (2008)Google Scholar
  16. 16.
    Doursat, R.: Morphogenetic engineering weds bio selforganization to human-designed systems. PerAda Mag. (2011)Google Scholar
  17. 17.
    Doursat, R.: The myriads of alife: importing complex systems and self-organization into engineering. In: Proceedings of the 3rd IEEE Symposium on Artificial Life (IEEE-ALIFE 2011), pp. xii-xix. IEEE (2011)Google Scholar
  18. 18.
    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 (1997)Google Scholar
  19. 19.
    Endy, D.: Foundations for engineering biology. Nature 438(7067), 449–453 (2005)CrossRefGoogle Scholar
  20. 20.
    Giavitto, J.L., Michel, O.: The topological structures of membrane computing. Fundamenta Informaticae 49(1–3), 123–145 (2002)MathSciNetMATHGoogle Scholar
  21. 21.
    Gierer, A., Meinhardt, H.: A theory of biological pattern formation. Biol. Cybern. 12(1), 30–39 (1972)Google Scholar
  22. 22.
    Goldstein, S., Campbell, J., Mowry, T.: Programmable matter. Computer 38(6), 99–101 (2005)CrossRefGoogle Scholar
  23. 23.
    Hebb, D.O.: The Organization of Behavior. Wiley, New York (1949)Google Scholar
  24. 24.
    Holland, J.H.: Adaptation in Natural and Artificial Systems, vol. 53. University of Michigan Press, Ann Arbor (1975)Google Scholar
  25. 25.
    Hopfield, J.J.: Neural networks and physical systems with emergent collective computational abilities. Proc. Natl. Acad. Sci. 79(8), 2554 (1982)MathSciNetCrossRefGoogle Scholar
  26. 26.
    Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of the IEEE International Conference on Neural Networks, vol. 4, pp. 1942–1948. IEEE (1995)Google Scholar
  27. 27.
    Kephart, J.O., Chess, D.M.: The vision of autonomic computing. Computer 36(1), 41–50 (2003)MathSciNetCrossRefGoogle Scholar
  28. 28.
    Knight, T.: Idempotent vector design for standard assembly of biobricks. Technical Report, DTIC Document (2003)Google Scholar
  29. 29.
    Kowaliw, T., Grogono, P., Kharma, N.: Bluenome: a novel developmental model of artificial morphogenesis. In: Genetic and Evolutionary Computation GECCO ’04, pp. 93–104. Springer (2004)Google Scholar
  30. 30.
    Lipson, H., Pollack, J.B.: Automatic design and manufacture of robotic lifeforms. Nature 406(6799), 974–978 (2000)CrossRefGoogle Scholar
  31. 31.
    Malsburg, C.: Organic computing. In: Würtz, R.P. (ed.) Organic Computing, Understanding Complex Systems, chap. The Organic Future of Information Technology, pp. 7–24. Springer, New York (2008)Google Scholar
  32. 32.
    Marzano, S., Aarts, E.: The New Everyday View on Ambient Intelligence. Uitgeverij 010 Publishers, Rotterdam (2003)Google Scholar
  33. 33.
    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. Academic Press, London (2003)Google Scholar
  34. 34.
    Minai, A.A., Braha, D., Bar-Yam, Y.: Complex engineered systems: science meets technology. In: Braha, D., Minai, A.A., Bar-Yam, Y. (eds.) Complex Engineered Systems: Science Meets Technology, Chap. Complex Engineered Systems: A New Paradigm, pp. 1–21. Springer, Cambridge (2006)Google Scholar
  35. 35.
    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
  36. 36.
    Newman, M.E.J.: Modularity and community structure in networks. Proc. Natl. Acad. Sci. 103(23), 8577–8582 (2006)CrossRefGoogle Scholar
  37. 37.
    Nunes de Castro, L.N.: Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications. CRC Press, Boca Raton (2006)Google Scholar
  38. 38.
    Pearson, J.E.: Complex patterns in a simple system. Science 261(5118), 189–192 (1993)CrossRefGoogle Scholar
  39. 39.
    Pfeifer, R., Bongard, J., Grand, S.: How the Body Shapes the Way We Think: A New View of Intelligence. The MIT Press, Cambridge (2006)Google Scholar
  40. 40.
    Rothemund, P.W.K.: Folding dna to create nanoscale shapes and patterns. Nature 440(7082), 297–302 (2006)CrossRefGoogle Scholar
  41. 41.
    Sayama, H.: Swarm chemistry. Artif. Life 15(1), 105–114 (2009)CrossRefGoogle Scholar
  42. 42.
    Sims, K.: Evolving 3d morphology and behavior by competition. Artif. life 1(4), 353–372 (1994)CrossRefGoogle Scholar
  43. 43.
    Stanley, K.O., Miikkulainen, R.: A taxonomy for artificial embryogeny. Artif. Life 9(2), 93–130 (2003)CrossRefGoogle Scholar
  44. 44.
    Stepney, S., Braunstein, S.L., Clark, J.A., Tyrrell, A., Adamatzky, A., Smith, R.E., Addis, T., Johnson, C., Timmis, J., Welch, P., Milner, R., Partridge, D.: Journeys in non-classical computation i: a grand challenge for computing research. Int. J. Parallel Emergent Distrib. Syst. 20(1), 5–19 (2005)MathSciNetMATHCrossRefGoogle Scholar
  45. 45.
    Tanenbaum, A.S., van Steen, M.: Distributed Systems: Principles and Paradigms. Prentice Hall, Upper Saddle River (2002)Google Scholar
  46. 46.
    Ulieru, M., Doursat, R.: Emergent engineering: a radical paradigm shift. Int. J. Auton. Adapt. Commun. Syst. 4(1), 39–60 (2011)CrossRefGoogle Scholar
  47. 47.
    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
  48. 48.
    Weiser, M.: Some computer science issues in ubiquitous computing. Commun. ACM 36(7), 75–84 (1993)CrossRefGoogle Scholar
  49. 49.
    Werfel, J., Nagpal, R.: Extended stigmergy in collective construction. IEEE Intell. Syst. 21(2), 20–28 (2006)CrossRefGoogle Scholar
  50. 50.
    Würtz, R.P.: Organic Computing. Springer, Berlin (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Complex Systems Institute, Paris Ile-de-France (ISC-PIF)CNRS & Ecole PolytechniqueParisFrance
  2. 2.Collective Dynamics of Complex Systems Research Group (CoCo), Departments of Bioengineering & Systems Science and Industrial EngineeringBinghamton University, SUNYBinghamtonUSA
  3. 3.Algorithmic, Complexity and Logic Laboratory (LACL), Department of Computer ScienceUniversité de Paris-Est CréteilCréteilFrance

Personalised recommendations