Computational matter: evolving computational functions in nanoscale materials

Haitze J. Broersma, Julian F. Miller, Stefano Nichele

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    Abstract

    Natural evolution has been manipulating the properties of proteins for billions of years. This ‘design process’ is completely different to conventional human design which assembles well-understood smaller parts in a highly principled way. In evolution-in-materio (EIM), researchers use evolutionary algorithms to define configurations and magnitudes of physical variables (e.g. voltages) which are applied to material systems so that they carry out useful computation. One of the advantages of this is that artificial evolution can exploit physical effects that are either too complex to understand or hitherto unknown. An EU funded project in Unconventional Computation called NASCENCE: Nanoscale Engineering of Novel Computation using Evolution, has the aim to model, understand and exploit the behaviour of evolved configurations of nanosystems (e.g. networks of nanoparticles, carbon nanotubes, liquid crystals) to solve computational problems. The project showed that it is possible to use materials to help find solutions to a number of well-known computational problems (e.g. TSP, Bin-packing, Logic gates, etc.).
    Original languageUndefined
    Title of host publicationAdvances in Unconventional Computing, Volume 2: Prototypes, Models and Algorithms
    EditorsAndrew Adamatzky
    Place of PublicationLondon
    PublisherSpringer
    Pages397-428
    Number of pages32
    ISBN (Print)978-3-319-33920-7
    DOIs
    Publication statusPublished - 2016

    Publication series

    NameEmergence, Complexity and Computation
    PublisherSpringer Verlag
    Number23
    Volume23
    ISSN (Print)2194-7287

    Keywords

    • EWI-27293
    • nanoparticle networks
    • computational matter
    • programmable nanosystems
    • METIS-319458
    • Evolution in materio
    • Genetic Algorithms
    • Unconventional computing
    • IR-102385

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