An adaptive network model for burnout and dreaming

Mathijs Maijer, Esra Solak, Jan Treur*

*Corresponding author for this work

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

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Abstract

As burnouts grow increasingly common, the necessity for a model describing burnout dynamics becomes increasingly apparent. The model discussed in this paper builds on previous research by adding dreams, a component that has been shown to have an adaptive regulating effect on emotions. The proposed model is a first-order adaptive temporal-causal network model, incorporating emotions, exercise, sleep, and dreams. The model was validated against given patterns found in empirical literature and it may be used to gain a better understanding of burnout dynamics.

Original languageEnglish
Title of host publicationComputational Science – ICCS 2020
Subtitle of host publication20th International Conference,Amsterdam, The Netherlands, June 3–5, 2020, Proceedings, Part I
EditorsValeria V. Krzhizhanovskaya, Gábor Závodszky, Michael H. Lees, Peter M.A. Sloot, Peter M.A. Sloot, Peter M.A. Sloot, Jack J. Dongarra, Sérgio Brissos, João Teixeira
PublisherSpringer
Pages342-356
Number of pages15
Volume1
ISBN (Electronic)9783030503710
ISBN (Print)9783030503703
DOIs
Publication statusPublished - 2020
Event20th International Conference on Computational Science, ICCS 2020 - Amsterdam, Netherlands
Duration: 3 Jun 20205 Jun 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12137 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Computational Science, ICCS 2020
CountryNetherlands
CityAmsterdam
Period3/06/205/06/20

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