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Computational Neuroscience Offers Hints for More General Machine Learning

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Artificial General Intelligence (AGI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10414))

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Abstract

Machine Learning has traditionally focused on narrow artificial intelligence - solutions for specific problems. Despite this, we observe two trends in the state-of-the-art: One, increasing architectural homogeneity in algorithms and models. Two, algorithms having more general application: New techniques often beat many benchmarks simultaneously. We review the changes responsible for these trends and look to computational neuroscience literature to anticipate future progress.

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Authors and Affiliations

  1. Incubator 491 Pty Ltd, Melbourne, Australia

    David Rawlinson & Gideon Kowadlo

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  1. David Rawlinson
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  2. Gideon Kowadlo
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Correspondence to David Rawlinson .

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Editors and Affiliations

  1. Australian National University , Canberra, Aust Capital Terr, Australia

    Tom Everitt

  2. OpenCog Foundation , Hong Kong, China

    Ben Goertzel

  3. St. Petersburg State University , St. Petersburg, Russia

    Alexey Potapov

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Rawlinson, D., Kowadlo, G. (2017). Computational Neuroscience Offers Hints for More General Machine Learning. In: Everitt, T., Goertzel, B., Potapov, A. (eds) Artificial General Intelligence. AGI 2017. Lecture Notes in Computer Science(), vol 10414. Springer, Cham. https://doi.org/10.1007/978-3-319-63703-7_12

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  • DOI: https://doi.org/10.1007/978-3-319-63703-7_12

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