A network-oriented adaptive agent model for learning regulation of a highly sensitive person’s response

Linh Tran, Jan Treur, Denice J. Tuinhof

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Inspired by the work of Elaine Aron, in this paper a human-like adaptive computational agent model of the internal processes of a highly sensitive person (HSP) is presented. This agent model was used to get a better understanding of what goes wrong in these internal processes once this person gets upset. A scenario is addressed where a highly sensitive person will get upset by an external stimulus and will not be able to calm down by herself. Yet in a social context the interaction with a second person (without high sensitivity) will calm the HSP down, thus contributing to regulation. To obtain an adaptive model a Hebbian learning connection was integrated. During interaction with a second person this Hebbian learning link will become stronger, which makes it possible for a HSP to become independent after some time and be able to regulate upsetting external stimuli all by herself.

LanguageEnglish
Title of host publicationAdvances in Practical Applications of Agents, Multi-Agent Systems, and Complexity
Subtitle of host publicationThe PAAMS Collection - 16th International Conference, PAAMS 2018, Proceedings
PublisherSpringer Verlag
Pages248-261
Number of pages14
ISBN (Electronic)9783319945804
ISBN (Print)9783319945798
DOIs
StatePublished - 2018
Event16th International Conference on Practical Applications of Agents, Multi-Agent Systems, PAAMS 2018 - Toledo, Spain
Duration: 20 Jun 201822 Jun 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10978 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Practical Applications of Agents, Multi-Agent Systems, PAAMS 2018
CountrySpain
CityToledo
Period20/06/1822/06/18

Fingerprint

Person
Hebbian Learning
Model
Internal
Learning
Interaction
Scenarios

Keywords

  • Hebbian learning
  • Highly sensitive person
  • Sensory processing sensitivity

Cite this

Tran, L., Treur, J., & Tuinhof, D. J. (2018). A network-oriented adaptive agent model for learning regulation of a highly sensitive person’s response. In Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection - 16th International Conference, PAAMS 2018, Proceedings (pp. 248-261). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10978 LNAI). Springer Verlag. DOI: 10.1007/978-3-319-94580-4_20
Tran, Linh ; Treur, Jan ; Tuinhof, Denice J./ A network-oriented adaptive agent model for learning regulation of a highly sensitive person’s response. Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection - 16th International Conference, PAAMS 2018, Proceedings. Springer Verlag, 2018. pp. 248-261 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{fac2aef3b58745db8fa3c7210ae14cd6,
title = "A network-oriented adaptive agent model for learning regulation of a highly sensitive person’s response",
abstract = "Inspired by the work of Elaine Aron, in this paper a human-like adaptive computational agent model of the internal processes of a highly sensitive person (HSP) is presented. This agent model was used to get a better understanding of what goes wrong in these internal processes once this person gets upset. A scenario is addressed where a highly sensitive person will get upset by an external stimulus and will not be able to calm down by herself. Yet in a social context the interaction with a second person (without high sensitivity) will calm the HSP down, thus contributing to regulation. To obtain an adaptive model a Hebbian learning connection was integrated. During interaction with a second person this Hebbian learning link will become stronger, which makes it possible for a HSP to become independent after some time and be able to regulate upsetting external stimuli all by herself.",
keywords = "Hebbian learning, Highly sensitive person, Sensory processing sensitivity",
author = "Linh Tran and Jan Treur and Tuinhof, {Denice J.}",
year = "2018",
doi = "10.1007/978-3-319-94580-4_20",
language = "English",
isbn = "9783319945798",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "248--261",
booktitle = "Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity",

}

Tran, L, Treur, J & Tuinhof, DJ 2018, A network-oriented adaptive agent model for learning regulation of a highly sensitive person’s response. in Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection - 16th International Conference, PAAMS 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10978 LNAI, Springer Verlag, pp. 248-261, 16th International Conference on Practical Applications of Agents, Multi-Agent Systems, PAAMS 2018, Toledo, Spain, 20/06/18. DOI: 10.1007/978-3-319-94580-4_20

A network-oriented adaptive agent model for learning regulation of a highly sensitive person’s response. / Tran, Linh; Treur, Jan; Tuinhof, Denice J.

Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection - 16th International Conference, PAAMS 2018, Proceedings. Springer Verlag, 2018. p. 248-261 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10978 LNAI).

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - A network-oriented adaptive agent model for learning regulation of a highly sensitive person’s response

AU - Tran,Linh

AU - Treur,Jan

AU - Tuinhof,Denice J.

PY - 2018

Y1 - 2018

N2 - Inspired by the work of Elaine Aron, in this paper a human-like adaptive computational agent model of the internal processes of a highly sensitive person (HSP) is presented. This agent model was used to get a better understanding of what goes wrong in these internal processes once this person gets upset. A scenario is addressed where a highly sensitive person will get upset by an external stimulus and will not be able to calm down by herself. Yet in a social context the interaction with a second person (without high sensitivity) will calm the HSP down, thus contributing to regulation. To obtain an adaptive model a Hebbian learning connection was integrated. During interaction with a second person this Hebbian learning link will become stronger, which makes it possible for a HSP to become independent after some time and be able to regulate upsetting external stimuli all by herself.

AB - Inspired by the work of Elaine Aron, in this paper a human-like adaptive computational agent model of the internal processes of a highly sensitive person (HSP) is presented. This agent model was used to get a better understanding of what goes wrong in these internal processes once this person gets upset. A scenario is addressed where a highly sensitive person will get upset by an external stimulus and will not be able to calm down by herself. Yet in a social context the interaction with a second person (without high sensitivity) will calm the HSP down, thus contributing to regulation. To obtain an adaptive model a Hebbian learning connection was integrated. During interaction with a second person this Hebbian learning link will become stronger, which makes it possible for a HSP to become independent after some time and be able to regulate upsetting external stimuli all by herself.

KW - Hebbian learning

KW - Highly sensitive person

KW - Sensory processing sensitivity

UR - http://www.scopus.com/inward/record.url?scp=85049380842&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85049380842&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-94580-4_20

DO - 10.1007/978-3-319-94580-4_20

M3 - Conference contribution

SN - 9783319945798

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 248

EP - 261

BT - Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity

PB - Springer Verlag

ER -

Tran L, Treur J, Tuinhof DJ. A network-oriented adaptive agent model for learning regulation of a highly sensitive person’s response. In Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection - 16th International Conference, PAAMS 2018, Proceedings. Springer Verlag. 2018. p. 248-261. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Available from, DOI: 10.1007/978-3-319-94580-4_20