TY - GEN
T1 - An adaptive network model for burnout and dreaming
AU - Maijer, Mathijs
AU - Solak, Esra
AU - Treur, Jan
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
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U2 - 10.1007/978-3-030-50371-0_25
DO - 10.1007/978-3-030-50371-0_25
M3 - Conference contribution
AN - SCOPUS:85087532062
SN - 9783030503703
VL - 1
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 342
EP - 356
BT - Computational Science – ICCS 2020
A2 - Krzhizhanovskaya, Valeria V.
A2 - Závodszky, Gábor
A2 - Lees, Michael H.
A2 - Sloot, Peter M.A.
A2 - Sloot, Peter M.A.
A2 - Sloot, Peter M.A.
A2 - Dongarra, Jack J.
A2 - Brissos, Sérgio
A2 - Teixeira, João
PB - Springer
T2 - 20th International Conference on Computational Science, ICCS 2020
Y2 - 3 June 2020 through 5 June 2020
ER -