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

37 Downloads (Pure)


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
Number of pages15
ISBN (Electronic)9783030503710
ISBN (Print)9783030503703
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


Conference20th International Conference on Computational Science, ICCS 2020


Dive into the research topics of 'An adaptive network model for burnout and dreaming'. Together they form a unique fingerprint.

Cite this