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An Adaptive Temporal-Causal Network Model for Enabling Learning of Social Interaction

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Highlights of Practical Applications of Cyber-Physical Multi-Agent Systems (PAAMS 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 722))

Abstract

In this study, an adaptive temporal-causal network model is presented for learning of basic skills for social interaction. It focuses on greeting a known person and how that relates to learning how to recognize a person from seeing his or her face. The model involves a Hebbian learning process. The model also addresses avoidance behavior related to enhanced sensory processing sensitivity. In scenarios persons without and with enhanced sensory processing sensitivity are compared. Mathematical analysis was performed to verify correctness of the model.

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Author information

Authors and Affiliations

  1. Behavioural Informatics Group, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Charlotte Commu, Mathilde Theelen & Jan Treur

Authors
  1. Charlotte Commu
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  2. Mathilde Theelen
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  3. Jan Treur
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Corresponding author

Correspondence to Jan Treur .

Editor information

Editors and Affiliations

  1. Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Madrid, Spain

    Javier Bajo

  2. Polytechnic Institute of Porto, Porto, Portugal

    Zita Vale

  3. University of Southern Denmark, Odense, Denmark

    Kasper Hallenborg

  4. University of Porto, Porto, Portugal

    Ana Paula Rocha

  5. Lille University of Science and Technology, Lille, France

    Philippe Mathieu

  6. Poznan University of Technology, Poznan, Poland

    Pawel Pawlewski

  7. Polytechnic University of Valencia, Valencia, Spain

    Elena Del Val

  8. University of Minho, Braga, Portugal

    Paulo Novais

  9. National Laboratory of Energy and Geology, Lisbon, Portugal

    Fernando Lopes

  10. National University of Colombia, Manizales, Caldas, Colombia

    Nestor D. Duque Méndez

  11. Polytechnic University of Valencia, Valencia, Spain

    Vicente Julián

  12. Malmö University, Malmo, Sweden

    Johan Holmgren

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Commu, C., Theelen, M., Treur, J. (2017). An Adaptive Temporal-Causal Network Model for Enabling Learning of Social Interaction. In: Bajo, J., et al. Highlights of Practical Applications of Cyber-Physical Multi-Agent Systems. PAAMS 2017. Communications in Computer and Information Science, vol 722. Springer, Cham. https://doi.org/10.1007/978-3-319-60285-1_22

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  • DOI: https://doi.org/10.1007/978-3-319-60285-1_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60284-4

  • Online ISBN: 978-3-319-60285-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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