An Adaptive Cognitive-Social Model for Mirroring and Social Bonding During Synchronous Joint Action

Michael Accetto, J. Treur, Valentina Villa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents an adaptive temporal-causal network model of human syn-chronization and bonding during a joint action. Two adaptive modelling princi-ples were adopted: the Hebbian learning principle for the mirroring process under-lying synchronisation, and the Homophily principle representing the social bond-ing. As validation reported experimental conditions were simulated. Mathematical analysis was performed to derive asymptotic properties and correctness.
LanguageEnglish
Title of host publicationProceedings of the 9th International Conference on Biologically Inspired Cognitive Architectures, BICA'18
PublisherSpringer
Number of pages11
StatePublished - 23 Aug 2018

Publication series

NameAdvances in Intelligent Systems and Computing

Cite this

Accetto, M., Treur, J., & Villa, V. (2018). An Adaptive Cognitive-Social Model for Mirroring and Social Bonding During Synchronous Joint Action. In Proceedings of the 9th International Conference on Biologically Inspired Cognitive Architectures, BICA'18 (Advances in Intelligent Systems and Computing). Springer.
Accetto, Michael ; Treur, J. ; Villa, Valentina. / An Adaptive Cognitive-Social Model for Mirroring and Social Bonding During Synchronous Joint Action. Proceedings of the 9th International Conference on Biologically Inspired Cognitive Architectures, BICA'18. Springer, 2018. (Advances in Intelligent Systems and Computing).
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title = "An Adaptive Cognitive-Social Model for Mirroring and Social Bonding During Synchronous Joint Action",
abstract = "This paper presents an adaptive temporal-causal network model of human syn-chronization and bonding during a joint action. Two adaptive modelling princi-ples were adopted: the Hebbian learning principle for the mirroring process under-lying synchronisation, and the Homophily principle representing the social bond-ing. As validation reported experimental conditions were simulated. Mathematical analysis was performed to derive asymptotic properties and correctness.",
author = "Michael Accetto and J. Treur and Valentina Villa",
year = "2018",
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Accetto, M, Treur, J & Villa, V 2018, An Adaptive Cognitive-Social Model for Mirroring and Social Bonding During Synchronous Joint Action. in Proceedings of the 9th International Conference on Biologically Inspired Cognitive Architectures, BICA'18. Advances in Intelligent Systems and Computing, Springer.

An Adaptive Cognitive-Social Model for Mirroring and Social Bonding During Synchronous Joint Action. / Accetto, Michael; Treur, J.; Villa, Valentina.

Proceedings of the 9th International Conference on Biologically Inspired Cognitive Architectures, BICA'18. Springer, 2018. (Advances in Intelligent Systems and Computing).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - An Adaptive Cognitive-Social Model for Mirroring and Social Bonding During Synchronous Joint Action

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AU - Treur,J.

AU - Villa,Valentina

PY - 2018/8/23

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AB - This paper presents an adaptive temporal-causal network model of human syn-chronization and bonding during a joint action. Two adaptive modelling princi-ples were adopted: the Hebbian learning principle for the mirroring process under-lying synchronisation, and the Homophily principle representing the social bond-ing. As validation reported experimental conditions were simulated. Mathematical analysis was performed to derive asymptotic properties and correctness.

M3 - Conference contribution

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BT - Proceedings of the 9th International Conference on Biologically Inspired Cognitive Architectures, BICA'18

PB - Springer

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Accetto M, Treur J, Villa V. An Adaptive Cognitive-Social Model for Mirroring and Social Bonding During Synchronous Joint Action. In Proceedings of the 9th International Conference on Biologically Inspired Cognitive Architectures, BICA'18. Springer. 2018. (Advances in Intelligent Systems and Computing).