ITU

Neuroevolution

Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review

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Neuroevolution. / Lehman, Joel; Miikkulainen, Risto.

In: Scholarpedia, Vol. 8, No. 6, 2013, p. 30977.

Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review

Harvard

Lehman, J & Miikkulainen, R 2013, 'Neuroevolution', Scholarpedia, vol. 8, no. 6, pp. 30977. https://doi.org/10.4249/scholarpedia.30977

APA

Vancouver

Author

Lehman, Joel ; Miikkulainen, Risto. / Neuroevolution. In: Scholarpedia. 2013 ; Vol. 8, No. 6. pp. 30977.

Bibtex

@article{ed89f18daf20455d8952fb7ee0122705,
title = "Neuroevolution",
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.",
author = "Joel Lehman and Risto Miikkulainen",
year = "2013",
doi = "10.4249/scholarpedia.30977",
language = "English",
volume = "8",
pages = "30977",
journal = "Scholarpedia Journal",
issn = "1941-6016",
publisher = "Scholarpedia",
number = "6",

}

RIS

TY - JOUR

T1 - Neuroevolution

AU - Lehman, Joel

AU - Miikkulainen, Risto

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

U2 - 10.4249/scholarpedia.30977

DO - 10.4249/scholarpedia.30977

M3 - Journal article

VL - 8

SP - 30977

JO - Scholarpedia Journal

JF - Scholarpedia Journal

SN - 1941-6016

IS - 6

ER -

ID: 80651895