Abstract
This article proposes experiments on decision making based on the “Winter Survival Task”, one of the scenarios most commonly applied in behavioral and psychological studies. The goal of the Task is to identify, out of a predefined list of 12 items, those that are most likely to increase the chances of survival after the crash of a plane in a polar area. In our experiments, 60 pairs of unacquainted individuals (120 subjects in total) negotiate a common choice of the items to be retained after that each subject has performed the task individually. The results of the negotiations are analyzed in causal terms and show that the choices made by the subjects individually act as a causal factor with respect to the outcome of the negotiation.
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References
Vinciarelli, A., Pantic, M., Bourlard, H.: Social Signal Processing: Survey of an emerging domain. Image and Vision Computing Journal 27(12), 1743–1759 (2009)
Vinciarelli, A., Pantic, M., Heylen, D., Pelachaud, C., Poggi, I., DÉrrico, F., Schroeder, M.: Bridging the gap between social animal and unsocial machine: A survey of social signal processing. IEEE Transactions on Affective Computing 3(1), 69–87 (2012)
Brunet, P., Cowie, R.: Towards a conceptual framework of research on social signal processing. Journal on Multimodal User Interfaces (to appear, 2012)
Mehu, M., Scherer, K.: A psycho-ethological approach to social signal processing. Cognitive Processing 13(2), 397–414 (2012)
Poggi, I., DÉrrico, F.: Social signals: a framework in terms of goals and beliefs. Cognitive Processing 13(2), 427–445 (2012)
Pearl, J.: Causal inference in statistics: An overview. Statistics Survey 3(1), 96–146 (2009)
Pearl, J.: Statistics and causal inference: A review. Test 12(2), 281–345 (2003)
Pearl, J.: Causality: Models, Reasoning and Inference. Cambridge University Press (2000)
Glymour, C., Scheines, R., Spirtes, P., Kelly, K.: Discovering causal structure: Artificial intelligence, philosophy of science, and statistical modeling. Academic Press (1987)
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Campo, M., Polychroniou, A., Salamin, H., Filippone, M., Vinciarelli, A. (2013). Towards Causal Modeling of Human Behavior. In: Apolloni, B., Bassis, S., Esposito, A., Morabito, F. (eds) Neural Nets and Surroundings. Smart Innovation, Systems and Technologies, vol 19. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35467-0_33
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DOI: https://doi.org/10.1007/978-3-642-35467-0_33
Publisher Name: Springer, Berlin, Heidelberg
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