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Swarm-Based Morphogenetic Artificial Life

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

Abstract

We present a swarm-based framework for designing and implementing morphogenetic artifacts that can grow, self-organize and self-repair in a fully decentralized manner. Artifacts are realized as swarms of multiple types of very simple, kinetically interacting particles with no elaborate sensing, computation, or communication capabilities. The proposed framework is based on our earlier work, Swarm Chemistry, a computational model of particle swarms where mobile particles with different kinetic properties interact with each other to produce dynamic structures and behaviors spontaneously. The features of emergent patterns are implicitly encoded through interactive evolutionary design methods into a set of kinetic parameter values, called a recipe. In this chapter, we summarize several extensions of the model for morphogenetic engineering and demonstrate a variety of morphogenetic processes that can be achieved by using simple particles with minimal capability. Specifically, we show (1) diversity of self-organizing patterns that can be generated by simple particle swarms in our framework, (2) robustness of those patterns against external perturbations, (3) growth and self-assembly by local information transmission between particles and their stochastic differentiation, and (4) self-repair by stochastic re-differentiation of particles.

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References

  1. Sayama, H.: Robust morphogenesis of robotic swarms. IEEE Comput. Intell. Mag. 5(3), 43–49 (2010)

    Article  Google Scholar 

  2. Doursat, R.: Organically grown architectures: creating decentralized, autonomous systems by embryomorphic engineering. In: Würtz, R.P. (ed.) Organic Computing, pp. 167–200. Springer, Heidelberg (2008)

    Google Scholar 

  3. Doursat, R., Sayama, H., Michel, O. (eds.): Abstracts of the first international workshop on morphogenetic engineering. (Complex Systems Institute, Paris, France, 2009). http://iscpif.fr/MEW2009

  4. von Neumann, J.: Theory of Self-Reproducing Automata. University of Illinois Press, Urbana (1966)

    Google Scholar 

  5. Langton, C.G.: Artificial life. In: Artificial Life: Proceedings of Interdisciplinary Workshop on the Synthesis and Simulation of Living Systems, pp. 1–47. Addison-Wesley, Redwood City (1989)

    Google Scholar 

  6. Langton, C.G. (ed.): Artificial Life—An Overview. MIT Press, Cambridge (1998)

    Google Scholar 

  7. Bedau, M.A., McCaskill, J.S., Packard, N.H., Rasmussen, S., Adami, C., Green, D.G., Ikegami, T., Kaneko, K., Ray, T.S.: Open problems in artificial life. Artif. Life 6, 363–376 (2000)

    Article  Google Scholar 

  8. Sipper, M.: Fifty years of research on self-replication: an overview. Artif. Life 4, 237–257 (1998)

    Article  Google Scholar 

  9. Suthakorn, J., Cushing, A.B., Chirikjian, G.S.: An autonomous self-replicating robotic system. In: Proceedings of 2003 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003), pp. 137–142 (2003)

    Google Scholar 

  10. Freitas, R.A., Merkle, R.C.: Kinematic Self-Replicating Machines. Landes Bioscience, Georgetown (2004)

    Google Scholar 

  11. Zykov, V., Mytilinaios, E., Adams, B., Lipson, H.: Self-reproducing machines. Nature 435, 163–164 (2005)

    Article  Google Scholar 

  12. Hutton, T.: Evolvable self-reproducing cells in a two-dimensional artificial chemistry. Artif. Life 13, 11–30 (2007)

    Article  Google Scholar 

  13. Yim, M., Shen, W.-M., Salemi, B., Rus, D., Moll, M., Lipson, H., Klavins, E., Chirikjian, G.S.: Modular self-reconfigurable robot systems: challenges and opportunities for the future. IEEE Robot. Autom. Mag. 14(1), 43–52 (2007)

    Google Scholar 

  14. Pfeifer, R., Lungarella, M., Iida, F.: Self-organization, embodiment, and biologically inspired robotics. Science 318, 1088–1093 (2007)

    Article  Google Scholar 

  15. Dorigo, M., et al.: Swarm-Bots project. http://www.swarm-bots.org/ (2001–2005)

  16. Mamei, M., Vasirani, M., Zambonelli, F.: Experiments of morphogenesis in swarms of simple mobile robots. App. Artif. Intel. 18, 903–919 (2004)

    Article  Google Scholar 

  17. Cheng, J., Cheng, W., Nagpal, R.: Robust and self-repairing formation control for swarms of mobile agents. In: Proceedins of 20th National Conference on Artificial Intelligence (AAAI), vol.1, pp.59–64 (2005)

    Google Scholar 

  18. Baldassarre, G., Parisi, D., Nolfi, S.: Distributed coordination of simulated robots based on self-organization. Artif. Life 12, 289–311 (2006)

    Article  Google Scholar 

  19. O’Grady, R., Christensen, A.L., Dorigo, M.: SWARMORPH: Multi-robot morphogenesis using directional self-assembly. IRIDIA Technical, Report No. TR/IRIDIA/2008-001 (2008)

    Google Scholar 

  20. Jin, Y., Guo, H., Meng, Y.: Robustness analysis and failure recovery for a bio-inspired self-organizing multi-robot system. In: Proceedings of Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2009), pp. 154–164 (2009)

    Google Scholar 

  21. Guo, H., Meng, Y., Jin, Y.: A cellular mechanism for multi-robot construction via evolutionary multi-objective optimization of a gene regulatory networks. BioSystems 98(3), 193–203 (2009)

    Article  Google Scholar 

  22. Kernbach, S., Thenius, R., Kernbach, O., Schmickl, T.: Reembodiment of honeybee aggregation behavior in artificial micro-robotic systems. Adapt. Behav. 17, 237–259 (2009)

    Article  Google Scholar 

  23. Sayama, H.: Decentralized control and interactive design methods for large-scale heterogeneous self-organizing swarms. In: Almeida e Costa, F. et al. (ed.) Advances in Artificial Life: Proceedings of Ninth European Conference on Artifificial Life, pp. 675–684. Springer, Heidelberg (2007)

    Google Scholar 

  24. Sayama, H.: Swarm chemistry. Artif. Life 15, 105–114 (2009)

    Article  Google Scholar 

  25. Dittrich, P., Ziegler, J., Banzhaf, W.: Artificial chemistries—A review. Artif. Life 7, 225–275 (2001)

    Article  Google Scholar 

  26. Reynolds, C.W.: Flocks, herds, and schools: a distributed behavioral model. Comput. Graph. 21(4), 25–34 (1987)

    Article  Google Scholar 

  27. Couzin, I.D., Krause, J., James, R., Ruxton, G.D., Franks, N.R.: Collective memory and spatial sorting in animal groups. J. Theor. Biol. 218, 1–11 (2002)

    Article  MathSciNet  Google Scholar 

  28. Kunz, H., Hemelrijk, C.K.: Artificial fish schools: collective effects of school size, body size, and body form. Artif. Life 9, 237–253 (2003)

    Article  Google Scholar 

  29. Hemelrijk, C.K., Kunz, H.: Density distribution and size sorting in fish schools: an individual-based model. Behav. Ecol. 16, 178–187 (2005)

    Article  Google Scholar 

  30. Newman, J., Sayama, H.: Effect of sensory blind zones on milling behavior in a dynamic self-propelled particle model. Phys. Rev. E 78, 011913 (2008)

    Article  Google Scholar 

  31. Vicsek, T., Czirok, A., Ben-Jacob, E., Cohen, I., Shochet, O.: Novel type of phase-transition in a system of self-driven particles. Phys. Rev. Lett. 75, 1226–1229 (1995)

    Article  Google Scholar 

  32. D’Orsogna, M.R., Chuang, Y.L., Bertozzi, A.L., Chayes, L.: Self-propelled particles with soft-core interactions: patterns, stability, and collapse. Phys. Rev. Lett. 96, 104302 (2006)

    Article  Google Scholar 

  33. Chuang, Y.L., D’Orsogna, M.R., Marthaler, D., Bertozzi, A.L., Chayes, L.S.: State transitions and the continuum limit for a 2D interacting, self-propelled particle system. Phys. D 232, 33–47 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  34. Chate, H., Ginelli, F., Gregoire, G., Raynaud, F.: Collective motion of self-propelled particles interacting without cohesion. Phys. Rev. E 77, 046113 (2008)

    Article  Google Scholar 

  35. Vicsek, T., Zafiris, A.: Collective motion. arXiv:1010.5017v1 (2010)

    Google Scholar 

  36. Takagi, H.: Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation. Proc. IEEE 89, 1275–1296 (2001)

    Article  Google Scholar 

  37. Sayama, H., Dionne, S., Laramee, C., Wilson, D.S.: Enhancing the architecture of interactive evolutionary design for exploring heterogeneous particle swarm dynamics: an in-class experiment. In: Proceedings of Second IEEE Symposium on Artificial Life (IEEE), pp. 85–91 (2009)

    Google Scholar 

  38. Bush, B., Sayama, H.: Hyperinteractive evolutionary computation. IEEE Trans. Evol. Comp. 15, 424–433 (2011)

    Article  Google Scholar 

  39. Sayama, H.; Swarm chemistry homepage. http://bingweb.binghamton.edu/~sayama/SwarmChemistry/ (2007)

  40. Paley, D.A., Leonard, N.E., Sepulchre, R.J., Couzin, I.D.: Spatial models of bistability in biological collectives. In: Proceedings of IEEE Conference of Decision and Control (2008)

    Google Scholar 

  41. Sayama, H.: Seeking open-ended evolution in swarm chemistry. In: Proceedings of Third IEEE Symposium of Artificial Life (IEEE), pp. 186–193 (2011)

    Google Scholar 

  42. Sayama, H., Wong, C.: Quantifying evolutionary dynamics of swarm chemistry. In: Tom Lenaerts et al. (eds.) Advances in Artificial Life: Proceedings of Eleventh European Conference on Artificial Life, pp. 729–730. MIT Press, France (2011)

    Google Scholar 

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Correspondence to Hiroki Sayama .

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Sayama, H. (2012). Swarm-Based Morphogenetic Artificial Life. In: Doursat, R., Sayama, H., Michel, O. (eds) Morphogenetic Engineering. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33902-8_8

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  • DOI: https://doi.org/10.1007/978-3-642-33902-8_8

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