Computational model for reward-based generation and maintenance of motivation

Fawad Taj; Michel C.A. Klein; Aart van Halteren

doi:10.1007/978-3-030-05587-5_5

Computational model for reward-based generation and maintenance of motivation

Fawad Taj^*, Michel C.A. Klein, Aart van Halteren

^*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

In this paper, a computational model for the motivation process is presented that takes into account the reward pathway for motivation generation and associative learning for maintaining motivation through Hebbian learning approach. The reward prediction error is used to keep motivation maintained. These aspects are backed by recent neuroscientific models and literature. Simulation experiments have been performed by creating scenarios for student learning through rewards and controlling their motivation through regulation. Mathematical analysis is provided to verify the dynamic properties of the model.

Original language	English
Title of host publication	Brain Informatics
Subtitle of host publication	International Conference, BI 2018, Proceedings
Editors	Yang Yang, Vicky Yamamoto, Shouyi Wang, Erick Jones, Jianzhong Su, Tom Mitchell, Leon Iasemidis
Publisher	Springer - Verlag
Pages	41-51
Number of pages	11
ISBN (Electronic)	9783030055875
ISBN (Print)	9783030055868
DOIs	https://doi.org/10.1007/978-3-030-05587-5_5
Publication status	Published - 2018
Event	International Conference on Brain Informatics, BI 2018 - Arlington, United States Duration: 7 Dec 2018 → 9 Dec 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11309 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Brain Informatics, BI 2018
Country/Territory	United States
City	Arlington
Period	7/12/18 → 9/12/18

Keywords

Cognitive modelling
Motivation
Reward-based learning

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10.1007/978-3-030-05587-5_5

Taj2018_Chapter_ComputationalModelForReward-BaFinal published version, 1.45 MBLicence: Article 25fa Dutch Copyright Act

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Taj, F., Klein, M. C. A., & van Halteren, A. (2018). Computational model for reward-based generation and maintenance of motivation. In Y. Yang, V. Yamamoto, S. Wang, E. Jones, J. Su, T. Mitchell, & L. Iasemidis (Eds.), Brain Informatics: International Conference, BI 2018, Proceedings (pp. 41-51). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11309 LNAI). Springer - Verlag. https://doi.org/10.1007/978-3-030-05587-5_5

Taj, Fawad ; Klein, Michel C.A. ; van Halteren, Aart. / Computational model for reward-based generation and maintenance of motivation. Brain Informatics: International Conference, BI 2018, Proceedings. editor / Yang Yang ; Vicky Yamamoto ; Shouyi Wang ; Erick Jones ; Jianzhong Su ; Tom Mitchell ; Leon Iasemidis. Springer - Verlag, 2018. pp. 41-51 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{7604644e292c4fe39f3c29a8eda3a098,

title = "Computational model for reward-based generation and maintenance of motivation",

abstract = "In this paper, a computational model for the motivation process is presented that takes into account the reward pathway for motivation generation and associative learning for maintaining motivation through Hebbian learning approach. The reward prediction error is used to keep motivation maintained. These aspects are backed by recent neuroscientific models and literature. Simulation experiments have been performed by creating scenarios for student learning through rewards and controlling their motivation through regulation. Mathematical analysis is provided to verify the dynamic properties of the model.",

keywords = "Cognitive modelling, Motivation, Reward-based learning",

author = "Fawad Taj and Klein, {Michel C.A.} and {van Halteren}, Aart",

year = "2018",

doi = "10.1007/978-3-030-05587-5_5",

language = "English",

isbn = "9783030055868",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer - Verlag",

pages = "41--51",

editor = "Yang Yang and Vicky Yamamoto and Shouyi Wang and Erick Jones and Jianzhong Su and Tom Mitchell and Leon Iasemidis",

booktitle = "Brain Informatics",

note = "International Conference on Brain Informatics, BI 2018 ; Conference date: 07-12-2018 Through 09-12-2018",

}

Taj, F, Klein, MCA & van Halteren, A 2018, Computational model for reward-based generation and maintenance of motivation. in Y Yang, V Yamamoto, S Wang, E Jones, J Su, T Mitchell & L Iasemidis (eds), Brain Informatics: International Conference, BI 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11309 LNAI, Springer - Verlag, pp. 41-51, International Conference on Brain Informatics, BI 2018, Arlington, United States, 7/12/18. https://doi.org/10.1007/978-3-030-05587-5_5

Computational model for reward-based generation and maintenance of motivation. / Taj, Fawad; Klein, Michel C.A.; van Halteren, Aart.
Brain Informatics: International Conference, BI 2018, Proceedings. ed. / Yang Yang; Vicky Yamamoto; Shouyi Wang; Erick Jones; Jianzhong Su; Tom Mitchell; Leon Iasemidis. Springer - Verlag, 2018. p. 41-51 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11309 LNAI).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Computational model for reward-based generation and maintenance of motivation

AU - Taj, Fawad

AU - Klein, Michel C.A.

AU - van Halteren, Aart

PY - 2018

Y1 - 2018

N2 - In this paper, a computational model for the motivation process is presented that takes into account the reward pathway for motivation generation and associative learning for maintaining motivation through Hebbian learning approach. The reward prediction error is used to keep motivation maintained. These aspects are backed by recent neuroscientific models and literature. Simulation experiments have been performed by creating scenarios for student learning through rewards and controlling their motivation through regulation. Mathematical analysis is provided to verify the dynamic properties of the model.

AB - In this paper, a computational model for the motivation process is presented that takes into account the reward pathway for motivation generation and associative learning for maintaining motivation through Hebbian learning approach. The reward prediction error is used to keep motivation maintained. These aspects are backed by recent neuroscientific models and literature. Simulation experiments have been performed by creating scenarios for student learning through rewards and controlling their motivation through regulation. Mathematical analysis is provided to verify the dynamic properties of the model.

KW - Cognitive modelling

KW - Motivation

KW - Reward-based learning

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U2 - 10.1007/978-3-030-05587-5_5

DO - 10.1007/978-3-030-05587-5_5

M3 - Conference contribution

AN - SCOPUS:85058542380

SN - 9783030055868

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

SP - 41

EP - 51

BT - Brain Informatics

A2 - Yang, Yang

A2 - Yamamoto, Vicky

A2 - Wang, Shouyi

A2 - Jones, Erick

A2 - Su, Jianzhong

A2 - Mitchell, Tom

A2 - Iasemidis, Leon

PB - Springer - Verlag

T2 - International Conference on Brain Informatics, BI 2018

Y2 - 7 December 2018 through 9 December 2018

ER -

Taj F, Klein MCA , van Halteren A. Computational model for reward-based generation and maintenance of motivation. In Yang Y, Yamamoto V, Wang S, Jones E, Su J, Mitchell T, Iasemidis L, editors, Brain Informatics: International Conference, BI 2018, Proceedings. Springer - Verlag. 2018. p. 41-51. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2018 Dec 7. doi: 10.1007/978-3-030-05587-5_5

Computational model for reward-based generation and maintenance of motivation

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