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Swarm-Based Morphogenetic Artificial Life

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Morphogenetic Engineering

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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Authors and Affiliations

  1. Collective Dynamics of Complex Systems Research Group (CoCo), Departments of Bioengineering and Systems Science and Industrial Engineering, Binghamton University, SUNY, Binghamton, NY, 13902-6000, USA

    Hiroki Sayama

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  1. Hiroki Sayama
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Correspondence to Hiroki Sayama .

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Editors and Affiliations

  1. Institut des Systèmes Complexes, Paris Ile-de-France, Ecole Polytechnique, rue Lhomond 57-59, Paris, 75005, France

    René Doursat

  2. Binghamton University, Dept. Bioengineering, State University of New York, Binghamton, 13902-6000, New York, USA

    Hiroki Sayama

  3. Faculté des Sciences et Technologie, Lab. LACL-EA 4219, Université Paris-Est Créteil, avenue due Général de Gaulle 61, Créteil Cedex, 94010, France

    Olivier Michel

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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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