Abstract
The paper focuses on prescriptive affective decision making in Ultimatum Game (UG). It describes preliminary results on incorporating emotional aspects into normative decision making. One of the players (responder) is modelled via Markov decision process. The responder’s reward function is the weighted combination of two components: economic and emotional. The first component represents pure monetary profit while the second one reflects overall emotional state of the responder. The proposed model is tested on simulated data.
Supported by GA16-09848S, LTC18075 and EU-COST Action CA16228.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
This is so-called Markov assumption.
References
MATLAB version 7.5.0 (R2007b): The MathWorks Inc., Natick, Massachusetts, USA (2010)
Binmore, K.G.: Game Theory and the Social Contract: Just Playing, vol. 2. The MIT Press, Cambridge (1998)
Bosman, R., van Winden, F.: Emotional hazard in a power-to-take experiment. Econ. J. 112(474), 147–169 (2002)
Capra, M.: Mood-driven behavior in strategic interactions. Am. Econ. Rev. 94(2), 367–372 (2004)
Cox, J.C., Friedman, D., Gjerstad, S.: A tractale model of reciprocity and fairness. Games Econ. Behav. 59(1), 17–45 (2007). https://doi.org/10.1016/j.geb.2006.05.001
Fehr, E., Schmidt, K.M.: A theory of fairness, competition, and cooperation. Q. J. Econ. 114(3), 817–868 (1999). https://doi.org/10.1162/003355399556151
Grecucci, A., Giorgetta, C., van’t Wout, M., Bonini, N., Sanfey, A.G.: Reappraising the ultimatum: an FMRI study of emotion regulation and decision making. Cereb. Cortex 23, 399–410 (2013)
Guth, W., Schmittberger, R., Schwarze, B.: An experimental analysis of ultimatum bargaining. J. Econ. Behav. Org. 3(4), 367–388 (1982)
Haselhuhn, M.P., Mellers, B.A.: Emotions and cooperation in economic games. Elsevier 23(1), 24–33 (2005). https://doi.org/10.1016/j.cogbrainres.2005.01.005
Livet, P.: Rational choice, neuroeconomy and mixed emotions. Philos. Trans. R. Soc. B 365, 259–269 (2010)
Loewenstein, G., Lerner, J.S.: The role of affect in decision making. In: Handbook of Affective Sciences, pp. 619–642. Oxford University Press (2003). (Chap. 31)
McGraw, A.P., Larsen, J.T., Kahneman, D., Schkade, D.: Comparing gains and losses. Psychol. Sci. 21(10), 1438–1445 (2010)
Puterman, M.L.: Markov Decision Processes. Wiley, Hoboken (1994)
Rabin, M.: Incorporating fairness into game theory and economics. Am. Econ. Rev. 83(5), 1281–1302 (1993)
Sanfey, A., Rilling, J., Aronson, J., Nystrom, L., Cohen, J.: The neural basis of economic decision-making in the ultimatum game. Science 300, 1755–1758 (2003)
Srivastava, J., Espinoza, F., Fedorikhin, A.: Coupling and decoupling of unfairness and anger in ultimatum bargaining. J. Behav. Decis. Making 22, 475–489 (2008). https://doi.org/10.1002/bdm.631
Tamarit, I., Sanchez, A.: Emotions and strategic behavior: the case of the ultimatum game. PloS One 11(7) (July 2016). https://doi.org/10.1371/journal.pone.0158733
Woodruffe-Peacock, C., Turnbull, G.M., Johnson, M.A., Elahi, N., Preston, G.C.: The quick mood scale: development of a simple mood assessment scale for clinical pharmacology studies. Hum. Psychopharmatology Clin. Exp. 13(1), 53–58 (1998)
Acknowledgement
We would like to thank Eliška Zugarová for comments that greatly influenced the manuscript. The authors express their gratitude to anonymous reviewers for the valuable suggestions.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Homolová, J., Černecka, A., Guy, T.V., Kárný, M. (2019). Affective Decision-Making in Ultimatum Game: Responder Case. In: Slavkovik, M. (eds) Multi-Agent Systems. EUMAS 2018. Lecture Notes in Computer Science(), vol 11450. Springer, Cham. https://doi.org/10.1007/978-3-030-14174-5_9
Download citation
DOI: https://doi.org/10.1007/978-3-030-14174-5_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-14173-8
Online ISBN: 978-3-030-14174-5
eBook Packages: Computer ScienceComputer Science (R0)