A Computational Agent Model for Hebbian Learning of Social Interaction

J. Treur

doi:10.1007/978-3-642-24955-6_2

A Computational Agent Model for Hebbian Learning of Social Interaction

J. Treur

Research output: Contribution to Journal › Article › Academic › peer-review

175 Downloads (Pure)

Abstract

In social interaction between two persons usually a person displays understanding of the other person. This may involve both nonverbal and verbal elements, such as bodily expressing a similar emotion and verbally expressing beliefs about the other person. Such social interaction relates to an underlying neural mechanism based on a mirror neuron system, as known within Social Neuroscience. This mechanism may show different variations over time. This paper addresses this adaptation over time. It presents a computational model capable of learning social responses, based on insights from Social Neuroscience. The presented model may provide a basis for virtual agents in the context of simulation-based training of psychotherapists, gaming, or virtual stories. © 2011 Springer-Verlag.

Original language	English
Pages (from-to)	9-19
Journal	Lecture Notes in Computer Science
Volume	7062
DOIs	https://doi.org/10.1007/978-3-642-24955-6_2
Publication status	Published - 2011
Event	18th International Conference on Neural Information Processing, ICONIP'11 - Berlin-Heidelberg Duration: 1 Jan 2011 → 1 Jan 2011

Bibliographical note

Proceedings title: Proceedings of the 18th International Conference on Neural Information Processing, ICONIP'11, Part I.
Publisher: Springer Verlag
Place of publication: Berlin-Heidelberg
Editors: B.L. Lu et al.

Access to Document

10.1007/978-3-642-24955-6_2

273456Final published version, 399 KB

Fingerprint Dive into the research topics of 'A Computational Agent Model for Hebbian Learning of Social Interaction'. Together they form a unique fingerprint.

Cite this

@article{fb0f595e74ec4c8ab6548316b383782e,

title = "A Computational Agent Model for Hebbian Learning of Social Interaction",

abstract = "In social interaction between two persons usually a person displays understanding of the other person. This may involve both nonverbal and verbal elements, such as bodily expressing a similar emotion and verbally expressing beliefs about the other person. Such social interaction relates to an underlying neural mechanism based on a mirror neuron system, as known within Social Neuroscience. This mechanism may show different variations over time. This paper addresses this adaptation over time. It presents a computational model capable of learning social responses, based on insights from Social Neuroscience. The presented model may provide a basis for virtual agents in the context of simulation-based training of psychotherapists, gaming, or virtual stories. {\textcopyright} 2011 Springer-Verlag.",

author = "J. Treur",

note = "Proceedings title: Proceedings of the 18th International Conference on Neural Information Processing, ICONIP'11, Part I. Publisher: Springer Verlag Place of publication: Berlin-Heidelberg Editors: B.L. Lu et al.; 18th International Conference on Neural Information Processing, ICONIP'11 ; Conference date: 01-01-2011 Through 01-01-2011",

year = "2011",

doi = "10.1007/978-3-642-24955-6_2",

language = "English",

volume = "7062",

pages = "9--19",

journal = "Lecture Notes in Computer Science",

issn = "0302-9743",

publisher = "Springer Verlag",

}

TY - JOUR

T1 - A Computational Agent Model for Hebbian Learning of Social Interaction

AU - Treur, J.

N1 - Proceedings title: Proceedings of the 18th International Conference on Neural Information Processing, ICONIP'11, Part I. Publisher: Springer Verlag Place of publication: Berlin-Heidelberg Editors: B.L. Lu et al.

PY - 2011

Y1 - 2011

N2 - In social interaction between two persons usually a person displays understanding of the other person. This may involve both nonverbal and verbal elements, such as bodily expressing a similar emotion and verbally expressing beliefs about the other person. Such social interaction relates to an underlying neural mechanism based on a mirror neuron system, as known within Social Neuroscience. This mechanism may show different variations over time. This paper addresses this adaptation over time. It presents a computational model capable of learning social responses, based on insights from Social Neuroscience. The presented model may provide a basis for virtual agents in the context of simulation-based training of psychotherapists, gaming, or virtual stories. © 2011 Springer-Verlag.

AB - In social interaction between two persons usually a person displays understanding of the other person. This may involve both nonverbal and verbal elements, such as bodily expressing a similar emotion and verbally expressing beliefs about the other person. Such social interaction relates to an underlying neural mechanism based on a mirror neuron system, as known within Social Neuroscience. This mechanism may show different variations over time. This paper addresses this adaptation over time. It presents a computational model capable of learning social responses, based on insights from Social Neuroscience. The presented model may provide a basis for virtual agents in the context of simulation-based training of psychotherapists, gaming, or virtual stories. © 2011 Springer-Verlag.

U2 - 10.1007/978-3-642-24955-6_2

DO - 10.1007/978-3-642-24955-6_2

M3 - Article

VL - 7062

SP - 9

EP - 19

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

T2 - 18th International Conference on Neural Information Processing, ICONIP'11

Y2 - 1 January 2011 through 1 January 2011

ER -