Abstract
Social norms characterize collective and acceptable group conducts in human society. Furthermore, some social norms emerge from interactions of agents or humans. To achieve agent autonomy and make norm satisfaction explainable, we include emotions into the normative reasoning process, which evaluates whether to comply or violate a norm. Specifically, before selecting an action to execute, an agent observes the environment and infers the state and consequences with its internal states after norm satisfaction or violation of a social norm. Both norm satisfaction and violation provoke further emotions, and the subsequent emotions affect norm enforcement. This paper investigates how modeling emotions affect the emergence and robustness of social norms via social simulation experiments. We find that an ability in agents to consider emotional responses to the outcomes of norm satisfaction and violation (1) promotes norm compliance; and (2) improves societal welfare.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ajmeri, N., Guo, H., Murukannaiah, P.K., Singh, M.P.: Robust norm emergence by revealing and reasoning about context: socially intelligent agents for enhancing privacy. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), pp. 28–34. IJCAI, Stockholm, July 2018. https://doi.org/10.24963/ijcai.2018/4
Ajmeri, N., Guo, H., Murukannaiah, P.K., Singh, M.P.: Elessar: ethics in norm-aware agents. In: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), pp. 16–24. IFAAMAS, Auckland, May 2020. https://doi.org/10.5555/3398761.3398769
Alfonso Espinosa, B.: Agents with Affective Traits for Decision-Making in Complex Environments. Ph.D. thesis, Universitat Politècnica de València (2017). https://doi.org/10.4995/Thesis/10251/90497
Argente, E., Del Val, E., Perez-Garcia, D., Botti, V.: Normative emotional agents: a viewpoint paper. IEEE Trans. Affect. Comput. (2020). https://doi.org/10.1109/TAFFC.2020.3028512
Barrett, L.F., Adolphs, R., Marsella, S., Martinez, A.M., Pollak, S.D.: Emotional expressions reconsidered: challenges to inferring emotion from human facial movements. Psychol. Sci. Public Interest 20(1), 1–68 (2019)
Bourgais, M., Taillandier, P., Vercouter, L.: BEN: an agent architecture for explainable and expressive behavior in social simulation. In: Calvaresi, D., Najjar, A., Schumacher, M., Främling, K. (eds.) EXTRAAMAS 2019. LNCS (LNAI), vol. 11763, pp. 147–163. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-30391-4_9
Broersen, J., Dastani, M., Hulstijn, J., Huang, Z., van der Torre, L.: The BOID architecture: conflicts between beliefs, obligations, intentions and desires. In: Proceedings of the 5th International Conference on Autonomous Agents, pp. 9–16 (2001). https://doi.org/10.1145/375735.375766
Chopra, A.K., Singh, M.P.: From social machines to social protocols: software engineering foundations for sociotechnical systems. In: Proceedings of the 25th International World Wide Web Conference, pp. 903–914. ACM, Montréal, April 2016. https://doi.org/10.1145/2872427.2883018
Cohen, J.: Statistical Power Analysis for the Behavioral Sciences, 2nd edn. Lawrence Erlbaum Associates, Hillsdale (1988)
Dell’Anna, D., Dastani, M., Dalpiaz, F.: Runtime revision of sanctions in normative multi-agent systems. Autonom. Agents Multi-Agent Syst. 34(2), 1–54 (2020). https://doi.org/10.1007/s10458-020-09465-8
Edwards, W.: The theory of decision making. Psychol. Bull. 51(4), 380 (1954). https://doi.org/10.1037/h0053870
Frantz, C., Pigozzi, G.: Modeling norm dynamics in multiagent systems. J. Appl. Log. - IfCoLoG J. Log. App. 5(2), 491–564 (2018)
Glass, G.V.: Primary, secondary, and meta-analysis of research. Educ. Res. 5(10), 3–8 (1976). https://doi.org/10.3102/0013189X005010003
Grissom, R.J., Kim, J.J.: Effect Sizes for Research: Univariate and Multivariate Applications. Routledge, Abingdon-on-Thames (2012). https://doi.org/10.4324/9780203803233
Kafalı, Ö., Ajmeri, N., Singh, M.P.: DESEN: specification of sociotechnical systems via patterns of regulation and control. ACM Trans. Softw. Eng. Methodol. (TOSEM). 29(1), 7:1–7:50 (2020). https://doi.org/10.1145/3365664
Kalia, A.K., Ajmeri, N., Chan, K., Cho, J.H., Adalı, S., Singh, M.P.: The interplay of emotions and norms in multiagent systems. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), pp. 371–377. IJCAI, Macau, August 2019. https://doi.org/10.24963/ijcai.2019/53
Keltner, D., Haidt, J.: Social functions of emotions at four levels of analysis. Cogn. Emotion 13(5), 505–521 (1999). https://doi.org/10.1080/026999399379168
de Lima, I.C.A., Nardin, L.G., Sichman, J.S.: Gavel: a sanctioning enforcement framework. In: Weyns, D., Mascardi, V., Ricci, A. (eds.) EMAS 2018. LNCS (LNAI), vol. 11375, pp. 225–241. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-25693-7_12
Marín-Morales, J., et al.: Affective computing in virtual reality: emotion recognition from brain and heartbeat dynamics using wearable sensors. Sci. Rep. 8(1), 1–15 (2018). https://doi.org/10.1038/s41598-018-32063-4
Marsella, S., Gratch, J., Petta, P.: Computational models of emotion. In: Scherer, K.R., Banziger, T., Roesch, E. (eds.) A Blueprint for Affective Computing: A Sourcebook and Manual, chap. 1.2, pp. 21–46. Oxford University Press (2010)
Marsella, S.C., Gratch, J.: EMA: a process model of appraisal dynamics. Cogn. Syst. Res. 10(1), 70–90 (2009). https://doi.org/10.1016/j.cogsys.2008.03.005
Masad, D., Kazil, J.: MESA: an agent-based modeling framework. In: Proceedings of the 14th PYTHON in Science Conference, pp. 53–60 (2015)
Milgram, S., Liberty, H.J., Toledo, R., Wackenhut, J.: Response to intrusion into waiting lines. J. Personal. Soc. Psychol. 51(4), 683 (1986). https://doi.org/10.1037/0022-3514.51.4.683
Moerland, T.M., Broekens, J., Jonker, C.M.: Emotion in reinforcement learning agents and robots: a survey. Mach. Learn. 107(2), 443–480 (2017). https://doi.org/10.1007/s10994-017-5666-0
Morris-Martin, A., De Vos, M., Padget, J.: Norm emergence in multiagent systems: a viewpoint paper. Autonom. Agents Multi-Agent Syst. 33(6), 706–749 (2019). https://doi.org/10.1007/s10458-019-09422-0
Murukannaiah, P.K., Ajmeri, N., Jonker, C.M., Singh, M.P.: New foundations of ethical multiagent systems. In: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), pp. 1706–1710. IFAAMAS, Auckland, May 2020. https://doi.org/10.5555/3398761.3398958
Nardin, L.G., et al.: Classifying sanctions and designing a conceptual sanctioning process model for socio-technical systems. Knowl. Eng. Rev. (KER) 31(2), 142–166 (2016). https://doi.org/10.1017/S0269888916000023
Ortony, A., Clore, G.L., Collins, A.: The Cognitive Structure of Emotions. Cambridge University Press, New York (1988). https://doi.org/10.1017/CBO9780511571299
Rao, A.S., Georgeff, M.P.: Modeling rational agents within a BDI-architecture. In: Proceedings of the 2nd International Conference on Principles of Knowledge Representation and Reasoning, pp. 473–484 (1991). https://doi.org/10.5555/3087158.3087205
Savarimuthu, B.T.R., Cranefield, S.: Norm creation, spreading and emergence: a survey of simulation models of norms in multi-agent systems. Multiagent Grid Syst. 7(1), 21–54 (2011)
von Scheve, C., Moldt, D., Fix, J., von Luede, R.: My agents love to conform: norms and emotion in the micro-macro link. Comput. Math. Organ. Theory 12(2–3), 81–100 (2006). https://doi.org/10.1007/s10588-006-9538-6
Schwarz, N.: Emotion, cognition, and decision making. Cogn. Emotion 14(4), 433–440 (2000). https://doi.org/10.1080/026999300402745
Simon, H.A.: The new science of management decision. Harper Brothers (1960). https://doi.org/10.1037/13978-000
Simon, H.A.: Motivational and emotional controls of cognition. Psychol. Rev. 74(1), 29–39 (1967). https://doi.org/10.1037/h0024127
Singh, M.P.: Norms as a basis for governing sociotechnical systems. ACM Trans. Intell. Syst. Technol. (TIST). 5(1), 21:1–21:23 (2013). https://doi.org/10.1145/2542182.2542203
Acknowledgments
STT and MPS thank the NSF for partial support under grant IIS-1908374.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this paper
Cite this paper
Tzeng, ST., Ajmeri, N., Singh, M.P. (2022). Noe: Norm Emergence and Robustness Based on Emotions in Multiagent Systems. In: Theodorou, A., Nieves, J.C., De Vos, M. (eds) Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XIV. COINE 2021. Lecture Notes in Computer Science(), vol 13239. Springer, Cham. https://doi.org/10.1007/978-3-031-16617-4_5
Download citation
DOI: https://doi.org/10.1007/978-3-031-16617-4_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-16616-7
Online ISBN: 978-3-031-16617-4
eBook Packages: Computer ScienceComputer Science (R0)