Decision Making under Acute Stress Modeled by an Adaptive Temporal-Causal Network Model
| Autor: | Seyed Sahand Mohammadi Ziabari, Jan Treur |
|---|---|
| Přispěvatelé: | Computer Science, Network Institute, Research Programmes - Computer Science |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
SDG 16 - Peace
Computer science Phase (waves) 02 engineering and technology Stress lcsh:QA75.5-76.95 Stress (mechanics) 03 medical and health sciences 0302 clinical medicine 0202 electrical engineering electronic engineering information engineering Acute stress Network model lcsh:T58.5-58.64 business.industry lcsh:Information technology SDG 16 - Peace Justice and Strong Institutions Adaptive temporal-causal network model Justice and Strong Institutions Hebbian theory 020201 artificial intelligence & image processing Artificial intelligence lcsh:Electronic computers. Computer science business Hebbian learning 030217 neurology & neurosurgery |
| Zdroj: | Vietnam Journal of Computer Science, Vol 7, Iss 4, Pp 433-452 (2020) Vietnam Journal of Computer Science, 7(4), 433-452. World Scientific Ziabari, S S M & Treur, J 2020, ' Decision Making under Acute Stress Modeled by an Adaptive Temporal-Causal Network Model ', Vietnam Journal of Computer Science, vol. 7, no. 4, pp. 433-452 . https://doi.org/10.1142/S2196888820500244 |
| ISSN: | 2196-8888 |
| Popis: | The influence of acute severe stress or extreme emotion based on a Network-Oriented modeling methodology has been addressed here. Adaptive temporal causal network model is an approach to address the phenomena with complexity which cannot be or hard to be explained in a real-world experiment. In the first phase, the suppression of the existing network connections as a consequence of the acute stress modeled and in the second phase relaxing the suppression by giving some time and starting a new learning of the decision making in accordance to presence of stress starts again. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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