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Functionalist Emotion Model in NARS

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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

Emotions play a crucial role in different cognitive functions, such as action selection and decision-making processes. This paper describes a new appraisal model for the emotion mechanism of NARS, an AGI system. Different from the previous appraisal model where emotions are triggered by the specific context, the new appraisal evaluates the relations between the system and its goals, based on a new set of criteria, including desirability, belief, and anticipation. Our work focuses on the functions of emotions and how emotional reactions could help NARS to improve its various cognitive capacities.

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References

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Author information

Authors and Affiliations

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

    Xiang Li, Patrick Hammer & Pei Wang

  2. Department of Psychology, Temple University, Philadelphia, USA

    Hongling Xie

Authors
  1. Xiang Li
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  2. Patrick Hammer
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  3. Pei Wang
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  4. Hongling Xie
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Corresponding authors

Correspondence to Patrick Hammer , Pei Wang or Hongling Xie .

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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Li, X., Hammer, P., Wang, P., Xie, H. (2018). Functionalist Emotion Model in NARS. 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_12

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  • DOI: https://doi.org/10.1007/978-3-319-97676-1_12

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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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