A Computational Model of Coping for Simulating Human Behavior in High-Stress Situations

Yongsatianchot, N. and Marsella, S. (2021) A Computational Model of Coping for Simulating Human Behavior in High-Stress Situations. In: 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS '21), 3-7 May 2021, pp. 1425-1433. ISBN 9781450383073

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Publisher's URL: https://dl.acm.org/doi/abs/10.5555/3463952.3464116


People often encounter high-stress situations. Modeling and being able to predict people's behavior in such situations, how they cope, is a critical research topic. To that end, we propose a computational model of coping that casts Lazarus' theory of coping into a Partial Observable Markov Decision Process (POMDP) framework. This includes an appraisal process that models the factors that lead to stress by assessing a person's relation to the environment and a coping process that models people's behavior in the face of such stress. This coping process includes problem-focused coping, whereby people seek to alter the external environment, and emotion-focused coping, whereby people alter their internal beliefs, goals, and intentions in the face of stress. We evaluate the model's assumptions and predictions in the context of a high-stress situation that is increasingly common, the extreme conditions of a hurricane. We collected human survey data from the last several years of major U.S. hurricanes to evaluate the features in the models used for appraisal calculation. Additionally, we conducted a controlled human-subject experiment simulating a hurricane experience to investigate the prediction of the model on how people change their beliefs and goals to cope with the situation. The results show that, as predicted by the model, the proposed model features are significantly associated with the evacuation decisions and post-decision people also change their beliefs and goals in the directions that align with their prior decisions. Lastly, we conduct a simulation study showing that the proposed model is qualitatively closer to the experiment data than the baseline models that do not incorporate coping effects.

Item Type:Conference Proceedings
Additional Information:The work is supported by the National Science Foundation under grant no. CMMI-1638234.
Glasgow Author(s) Enlighten ID:Yongsatianchot, Nutchanon and Marsella, Professor Stacy
Authors: Yongsatianchot, N., and Marsella, S.
College/School:College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
College of Science and Engineering

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