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Elements of Cognition for General Intelligence

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Artificial General Intelligence (AGI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13921))

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Abstract

What can artificial intelligence learn from the cognitive sciences? We review some fundamental aspects of how human cognition works and relate it to different brain structures and their function. A central theme is that cognition is very different from how it is envisioned in classical artificial intelligence which offers a novel path toward intelligent systems that in many ways is both simpler and more attainable. We also argue that artificial intelligent systems takes more than a single silver bullet. It requires a large number of interacting subsystem that are coupled to both the body and to the environment. We argue for an approach to artificial general intelligence based on a faithful reproduction of known brain processes in a system-level model that incorporates a large number of components modelled after the human brain.

This work was partially supported by the Wallenberg AI, Autonomous Systems and Software Program - Humanities and Society (WASP-HS) funded by the Marianne and Marcus Wallenberg Foundation and the Marcus and Amalia Wallenberg Foundation.

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Authors and Affiliations

  1. Lund University Cognitive Science, Lund, Sweden

    Christian Balkenius, Birger Johansson & Trond A. Tjøstheim

Authors
  1. Christian Balkenius
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  2. Birger Johansson
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  3. Trond A. Tjøstheim
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Corresponding author

Correspondence to Christian Balkenius .

Editor information

Editors and Affiliations

  1. Department of Psychology, Stockholm University, Stockholm, Sweden

    Patrick Hammer

  2. Örebro University, Örebro, Sweden

    Marjan Alirezaie

  3. University of Gothenburg, Gothenburg, Sweden

    Claes Strannegård

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Balkenius, C., Johansson, B., Tjøstheim, T.A. (2023). Elements of Cognition for General Intelligence. In: Hammer, P., Alirezaie, M., Strannegård, C. (eds) Artificial General Intelligence. AGI 2023. Lecture Notes in Computer Science(), vol 13921. Springer, Cham. https://doi.org/10.1007/978-3-031-33469-6_2

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  • DOI: https://doi.org/10.1007/978-3-031-33469-6_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-33468-9

  • Online ISBN: 978-3-031-33469-6

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