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Behavior-Finding: Morphogenetic Designs Shaped by Function

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Morphogenetic Engineering

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

Abstract

Evolution has shaped an incredible diversity of multicellular living organisms, whose complex forms are self-made through a robust developmental process. This fundamental combination of biological evolution and development has served as an inspiration for novel engineering design methodologies, with the goal to overcome the scalability problems suffered by classical top-down approaches. Top-down methodologies are based on the manual decomposition of the design into modular, independent subunits. In contrast, recent computational morphogenetic techniques have shown that they were able to automatically generate truly complex innovative designs. Algorithms based on evolutionary computation and artificial development have been proposed to automatically design both the structures, within certain constraints, and the controllers that optimize their function. However, the driving force of biological evolution does not resemble an enumeration of design requirements, but much rather relies on the interaction of organisms within the environment. Similarly, controllers do not evolve nor develop separately, but are woven into the organism’s morphology. In this chapter, we discuss evolutionary morphogenetic algorithms inspired by these important aspects of biological evolution. The proposed methodologies could contribute to the automation of processes that design “organic” structures, whose morphologies and controllers are intended to solve a functional problem. The performance of the algorithms is tested on a class of optimization problems that we call behavior-finding. These challenges are not explicitly based on morphology or controller constraints, but only on the solving abilities and efficacy of the design. Our results show that morphogenetic algorithms are well suited to behavior-finding.

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Authors and Affiliations

  1. Biology Department and Tufts Center for Regenerative and Developmental Biology, Tufts University, Medford, MA, 02155, USA

    Daniel Lobo

  2. Research Group in Biomimetics (GEB), Department of Computer Science, Universidad de Málaga, 29590 , Málaga, Spain

    Jose David Fernández & Francisco J. Vico

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  1. Daniel Lobo
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  2. Jose David Fernández
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  3. Francisco J. Vico
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Correspondence to Daniel Lobo .

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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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Lobo, D., Fernández, J.D., Vico, F.J. (2012). Behavior-Finding: Morphogenetic Designs Shaped by Function. 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_17

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  • DOI: https://doi.org/10.1007/978-3-642-33902-8_17

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