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Morphogenesis as a Collective Decision of Agents Competing for Limited Resource: A Plants Approach

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Swarm Intelligence (ANTS 2018)

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Abstract

Competition for limited resource is a common concept in many artificial and natural collective systems. In plants, the common resources – water, minerals and the products of photosynthesis – are a subject of competition for individual branches striving for growth. The competition is realized via a dynamic vascular system resulting in the dynamic morphology of the plant that is adapting to its environment. In this paper, a distributed morphogenesis algorithm inspired by the competition for limited resources in plants is described and is validated in directing the growth of a physical structure made out of braided modules. The effects of different parameters of the algorithm on the growth behavior of the structure are discussed analytically and similar effects are demonstrated in the physical system.

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References

  1. Bennett, T., Hines, G., Leyser, O.: Canalization: what the flux? Trends Genet. 30(2), 41–48 (2014)

    Article  Google Scholar 

  2. Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, Oxford (1999)

    MATH  Google Scholar 

  3. Bonabeau, E., Sobkowski, A., Theraulaz, G., Deneubourg, J.L.: Adaptive task allocation inspired by a model of division of labor in social insects. In: Biocomputing and Emergent Computation: Proceedings of BCEC97, pp. 36–45. World Scientific Press (1997)

    Google Scholar 

  4. Camazine, S., et al.: Self-organizing Biological Systems. Princeton University Press, Princeton (2001)

    Google Scholar 

  5. Campo, A., et al.: Artificial pheromone for path selection by a foraging swarm of robots. Biol. Cybern. 103(5), 339–352 (2010)

    Article  Google Scholar 

  6. Clearwater, S.H. (ed.): Market-Based Control: A Paradigm for Distributed Resource Allocation. World Scientific Publishing Co., Inc., River Edge (1996)

    Google Scholar 

  7. Deconinck, G., Craemer, K.D., Claessens, B.: Combining market-based control with distribution grid constraints when coordinating electric vehicle charging. Engineering 1(4), 453–465 (2015)

    Article  Google Scholar 

  8. Detrain, C., Deneubourg, J.L.: Self-organized structures in a superorganism: do ants like molecules? Phys. Life Rev. 3(3), 162–187 (2006)

    Article  Google Scholar 

  9. Dorigo, M., Maniezzo, V., Colorni, A.: Ant system: optimization by a colony of cooperating agents. Trans. Syst. Man Cyber. Part B 26(1), 29–41 (1996)

    Article  Google Scholar 

  10. Doursat, R., Sánchez, C., Dordea, R., Fourquet, D., Kowaliw, T.: Embryomorphic engineering: emergent innovation through evolutionary development. In: Doursat, R., Sayama, H., Michel, O. (eds.) Morphogenetic Engineering. Understanding Complex Systems, pp. 275–311. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33902-8_11

    Chapter  Google Scholar 

  11. Ferrante, E., Turgut, A.E., Duenez-Guzman, E., Dorigo, M., Wenseleers, T.: Evolution of self-organized task specialization in robot swarms. PLOS Comput. Biol. 11(8), 1–21 (2015)

    Article  Google Scholar 

  12. Goodwin, B.: How the Leopard Changed its Spots: The Evolution of Complexity. Princeton University Press, Princeton (2001)

    Google Scholar 

  13. Hamann, H., et al.: Flora robotica - an architectural system combining living natural plants and distributed robots. arXiv preprint arXiv:1709.04291 (2017)

  14. Hamann, H.: Swarm Robotics: A Formal Approach. Springer, Berlin (2018). https://doi.org/10.1007/978-3-319-74528-2

    Book  Google Scholar 

  15. Hofstadler, D.N., et al.: Artificial plants - vascular morphogenesis controller-guided growth of braided structures. arXiv preprint arXiv:1804.06343 (2018)

  16. Hornby, G.S., Pollack, J.B.: Body-brain co-evolution using l-systems as a generative encoding. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), pp. 868–875. Morgan Kaufmann, San Francisco, July–November 2001

    Google Scholar 

  17. Huberman, B.A., Hogg, T.: Distributed computation as an economic system. J. Econ. Perspect. 9(1), 141–152 (1995)

    Article  Google Scholar 

  18. Karsai, I., Schmickl, T.: Regulation of task partitioning by a “common stomach”: a model of nest construction in social wasps. Behav. Ecol. 22, 819–830 (2011)

    Article  Google Scholar 

  19. Kowaliw, T., Banzhaf, W.: Mechanisms for complex systems engineering through artificial development. In: Doursat, R., Sayama, H., Michel, O. (eds.) Morphogenetic Engineering. Understanding Complex Systems. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33902-8_13

    Chapter  Google Scholar 

  20. Kurose, J.F., Simha, R.: A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Trans. Comput. 38(5), 705–717 (1989)

    Article  Google Scholar 

  21. Leyser, O.: Auxin, self-organisation, and the colonial nature of plants. Curr. Biol. 21(9), R331–R337 (2011)

    Article  Google Scholar 

  22. Lindenmayer, A.: Developmental algorithms for multicellular organisms: a survey of L-systems. J. Theor. Biol. 54(1), 3–22 (1975)

    Article  MathSciNet  Google Scholar 

  23. Murray, J.D.: On the mechanochemical theory of biological pattern formation with application to vasculogenesis. Comptes Rendus Biol. 326(2), 239–252 (2003)

    Article  Google Scholar 

  24. Payton, D., Daily, M., Estowski, R., Howard, M., Lee, C.: Pheromone robotics. Auton. Robot. 11(3), 319–324 (2001)

    Article  Google Scholar 

  25. Sachs, T.: The control of the patterned differentiation of vascular tissues. Adv. Bot. Res. 9, 151–262 (1981)

    Article  Google Scholar 

  26. Sims, K.: Evolving 3D morphology and behavior by competition. In: Brooks, R., Maes, P. (eds.) Artificial Life IV, pp. 28–39. MIT Press (1994)

    Google Scholar 

  27. Sperati, V., Trianni, V., Nolfi, S.: Self-organised path formation in a swarm of robots. Swarm Intell. 5(2), 97–119 (2011)

    Article  Google Scholar 

  28. Turing, A.M.: The chemical basis of morphogenesis. Philos. Trans. R. Soc. London. Ser. B Biol. Sci. B237(641), 37–72 (1952)

    Article  MathSciNet  Google Scholar 

  29. Waldspurger, C.A., Hogg, T., Huberman, B.A., Kephart, J.O., Stornetta, S.: Spawn: a distributed computational economy. IEEE Trans. Softw. Eng. 18(2), 103–117 (1992)

    Article  Google Scholar 

  30. Zahadat, P., Hahshold, S., Thenius, R., Crailsheim, K., Schmickl, T.: From honeybees to robots and back: division of labor based on partitioning social inhibition. Bioinspiration Biomim. 10(6), 066005 (2015)

    Article  Google Scholar 

  31. Zahadat, P., Hofstadler, D.N., Schmickl, T.: Development of morphology based on resource distribution: finding the shortest path in a maze by vascular morphogenesis controller. In: 14th European Conference on Artificial Life (ECAL-2017), vol. 14, pp. 428–429 (2017)

    Google Scholar 

  32. Zahadat, P., Hofstadler, D.N., Schmickl, T.: Vascular morphogenesis controller: a generative model for developing morphology of artificial structures. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2017, pp. 163–170. ACM, New York (2017)

    Google Scholar 

  33. Zahadat, P., Schmickl, T.: Generation of diversity in a reaction-diffusion-based controller. Artif. Life 20(3), 319–342 (2014)

    Article  Google Scholar 

  34. Zahadat, P., Schmickl, T.: Division of labor in a swarm of autonomous underwater robots by improved partitioning social inhibition. Adapt. Behav. 24(2), 87–101 (2016)

    Article  Google Scholar 

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Acknowledgments

This work was supported by EU-H2020 project ‘florarobotica’, no. 640959.

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Correspondence to Payam Zahadat .

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Zahadat, P., Hofstadler, D.N., Schmickl, T. (2018). Morphogenesis as a Collective Decision of Agents Competing for Limited Resource: A Plants Approach. In: Dorigo, M., Birattari, M., Blum, C., Christensen, A., Reina, A., Trianni, V. (eds) Swarm Intelligence. ANTS 2018. Lecture Notes in Computer Science(), vol 11172. Springer, Cham. https://doi.org/10.1007/978-3-030-00533-7_7

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  • DOI: https://doi.org/10.1007/978-3-030-00533-7_7

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