Abstract
In this paper, the goal is to model both the self-control and the emotion regulation dynamics involved in the process of procrastination. This is done by means of a temporal-causal network, incorporating learning and control of the learning. Additionally, the effect of stress regulation-therapy on the process of procrastination was investigated. The model’s base level implementation was verified by making sure the aggregated impact matches the node values for certain stationary points and the model’s Hebbian learning behaviour was also mathematically shown to be correctly implemented. The results proved this model’s ability to model different types of individuals, all with different stress sensitivities. Therapy was also shown to be greatly beneficial.
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Moulie, H., van den Berg, R., Treur, J. (2021). An Adaptive Network Model for Procrastination Behaviour Including Self-regulation and Emotion Regulation. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12742. Springer, Cham. https://doi.org/10.1007/978-3-030-77961-0_44
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