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Resource-Constrained Social Evidence Based Cognitive Model for Empathy-Driven Artificial Intelligence

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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

Working model of social aspects of human and non-human intelligence is required for social embodiment of artificial general intelligence systems to explain, predict and manage behavioral patterns in multi-agent communities. For this purpose, we propose implementation of resource-constrained social evidence based model and discuss possible implications of its application.

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Acknowledgements

This work was inspired by earlier ideas of Ben Goertzel, Jeff Pressing, Cassio Pennachin and Pei Wang in the course of Webmind project targeted to build artificial psyche in 1998–2001.

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Authors and Affiliations

  1. Aigents Group, Novosibirsk, Russia

    Anton Kolonin

  2. SingularityNET Foundation, Amsterdam, Netherlands

    Anton Kolonin

Authors
  1. Anton Kolonin
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Correspondence to Anton Kolonin .

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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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Kolonin, A. (2018). Resource-Constrained Social Evidence Based Cognitive Model for Empathy-Driven Artificial Intelligence. 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_10

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  • DOI: https://doi.org/10.1007/978-3-319-97676-1_10

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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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