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International Conference on Theory and Practice of Natural Computing

TPNC 2015: Theory and Practice of Natural Computing pp 3–19Cite as

EvoSphere: The World of Robot Evolution

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9477))

Abstract

In this paper I describe EvoSphere, a tangible realization of the general Evolution of Things concept. EvoSphere can be used as a research platform to study the evolution of intelligent machines for practical as well as theoretical purposes. On the one hand, it can be used to develop robots that are hard to obtain with traditional design and optimization techniques and it can deliver original solutions that are unlikely to be conceived by a human designer. On the other hand, EvoSphere forms an evolving ecosystem that enables fundamental research into evolution and embodied intelligence. The use of real hardware is a pivotal feature as it avoids the reality gap and guarantees that the evolved solutions are physically feasible. On the long term, EvoSphere technology can pave the way for robot populations that evolve ‘in the wild’ and can adapt to unforeseen and changing circumstances.

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Notes

  1. 1.

    http://tedxtalks.ted.com/video/TEDxDanubia-2011-goston-Eiben-T.

  2. 2.

    https://www.cyberbotics.com.

  3. 3.

    There exist systems that mix the two in a certain way. The idea is that the principal method is a traditional digital EA with simulated fitness evaluations, but every now and then an individual in the population is physically constructed and evaluated in the real world.

  4. 4.

    The paper [11] illustrated the components of this framework one by one using the modular robots of the Symbrion project. However, Symbrion was not aiming at physically evolving morphologies and the components of the ToL have not been integrated.

  5. 5.

    The alternative is offline evolution during the design stage of the robots. See [8] and Chap. 17 in [10] for a discussion.

  6. 6.

    http://www.karlsims.com/evolved-virtual-creatures.html.

  7. 7.

    A simple example is to use NN controllers with inheritable topology and learnable weights.

  8. 8.

    These steps may need to be revised for radically different types of robots, for instance soft robots with novel forms of control and actuation, but there will always be a list of such steps.

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Authors and Affiliations

  1. VU University Amsterdam, Amsterdam, The Netherlands

    A. E. Eiben

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  1. A. E. Eiben
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Correspondence to A. E. Eiben .

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Editors and Affiliations

  1. Research Group on Mathematical Linguistics, Universitat Rovira i Virgili, Tarragona, Spain

    Adrian-Horia Dediu

  2. European Centre for Soft Computing, Asturias, Spain

    Luis Magdalena

  3. Research Group on Mathematical Linguistics, Universitat Rovira i Virgili, Tarragona, Spain

    Carlos Martín-Vide

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Eiben, A.E. (2015). EvoSphere: The World of Robot Evolution. In: Dediu, AH., Magdalena, L., Martín-Vide, C. (eds) Theory and Practice of Natural Computing. TPNC 2015. Lecture Notes in Computer Science(), vol 9477. Springer, Cham. https://doi.org/10.1007/978-3-319-26841-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-26841-5_1

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  • Online ISBN: 978-3-319-26841-5

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