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Perception from an AGI Perspective

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Artificial General Intelligence (AGI 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10999))

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Abstract

This paper argues that according to the relevant discoveries of cognitive science, in AGI systems perception should be subjective, active, and unified with other processes. This treatment of perception is fundamentally different from the mainstream approaches in computer vision and machine learning, where perception is taken to be objective, passive, and modular. The conceptual design of perception in the AGI system NARS is introduced, where the three features are realized altogether. Some preliminary testing cases are used to show the features of this novel approach.

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Author information

Authors and Affiliations

  1. Department of Computer and Information Sciences, Temple University, Philadelphia, USA

    Pei Wang & Patrick Hammer

Authors
  1. Pei Wang
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  2. Patrick Hammer
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Corresponding author

Correspondence to Pei Wang .

Editor information

Editors and Affiliations

  1. Adams State University, Alamosa, Colorado, USA

    Matthew Iklé

  2. Odessa Competence Center for Artificial Intelligence (OCCAM), Odessa, Ukraine

    Arthur Franz

  3. Hokkaido University, Sapporo, Japan

    Rafal Rzepka

  4. SingularityNET; OpenCog; Hanson Robotics, Hong Kong, China

    Ben Goertzel

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Wang, P., Hammer, P. (2018). Perception from an AGI Perspective. In: Iklé, M., Franz, A., Rzepka, R., Goertzel, B. (eds) Artificial General Intelligence. AGI 2018. Lecture Notes in Computer Science(), vol 10999. Springer, Cham. https://doi.org/10.1007/978-3-319-97676-1_25

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  • DOI: https://doi.org/10.1007/978-3-319-97676-1_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97675-4

  • Online ISBN: 978-3-319-97676-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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