@inproceedings{459bb022e43647fb85ee48593218af37,
title = "An adaptive temporal-causal network model for decision making under acute stress",
abstract = "In recent literature from Neuroscience the adaptive role of the effects of stress on decision making is highlighted. The problem addressed in this paper is how that can be modelled computationally. The presented adaptive temporal-causal network model addresses the suppression of the existing network connections in a first phase as a result of the acute stress, and then as a second phase relaxing the suppression after some time and give room to start new learning of the decision making in the context of the stress again.",
keywords = "Adaptive temporal-causal network model, Hebbian learning, Stress",
author = "Jan Treur and {Mohammadi Ziabari}, {S. Sahand}",
year = "2018",
doi = "10.1007/978-3-319-98446-9_2",
language = "English",
isbn = "9783319984452",
volume = "2",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer/Verlag",
pages = "13--25",
editor = "Nguyen, {Ngoc Thanh} and Bogdan Trawinski and Elias Pimenidis and Zaheer Khan",
booktitle = "Computational Collective Intelligence",
note = "10th International Conference on Computational Collective Intelligence, ICCCI 2018 ; Conference date: 05-09-2018 Through 07-09-2018",
}