Neuroevolution

Joel Lehman, Risto Miikkulainen

    Publikation: Artikel i tidsskrift og konference artikel i tidsskriftTidsskriftartikelForskningpeer review

    Abstract

    Neuroevolution is a machine learning technique that applies evolutionary algorithms to construct artificial neural networks, taking inspiration from the evolution of biological nervous systems in nature. Compared to other neural network learning methods, neuroevolution is highly general; it allows learning without explicit targets, with only sparse feedback, and with arbitrary neural models and network structures. Neuroevolution is an effective approach to solving reinforcement learning problems, and is most commonly applied in evolutionary robotics and artificial life.
    OriginalsprogEngelsk
    TidsskriftScholarpedia
    Vol/bind8
    Udgave nummer6
    Sider (fra-til)30977
    Antal sider1
    ISSN1941-6016
    DOI
    StatusUdgivet - 2013

    Emneord

    • Neuroevolution
    • Evolutionary algorithms
    • Artificial neural networks
    • Reinforcement learning
    • Evolutionary robotics

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