Abstract
This paper studies compromise, which is the tendency of agents to move their opinions towards those of agents they interact with, trying to reach consensus. Compromise is one of the most important phenomena in the study of opinion dynamics, and this paper presents two analytic models to study it. First, agents are considered deterministic and a preliminary model of the effects of compromise is derived. Then, the model is generalized to give agents some level of autonomy by modelling their behaviour in terms of a stochastic process. Both models are analytic and they can be used to study collective properties of multi-agent systems starting from the details of single interactions among agents. Analytic results concerning the conservation of the average opinion for both models are verified by simulation in the last part of the paper.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Abelson, R.P.: Mathematical models of the distribution of attitudes under controversy. In: Frederiksen, N., Gulliksen, H. (eds.) Contributions to Mathematical Psychology, pp. 141–160. Holt, Rinehart and Winston, New York (1964)
Bergenti, F., Monica, S.: Analytic study of opinion dynamics in multi-agent systems with two classes of agents. In: Proceedings of 17th Workshop Dagli Oggetti agli Agenti (WOA 2016). CEUR Workshop Proceedings, vol. 1664, pp. 17–22. RWTH Aachen (2016)
Bonabeau, E.: Agent-based modeling: methods and techniques for simulating human systems. Proc. Natl. Acad. Sci. 3, 7280–7287 (2002)
Galam, S., Gefen, Y., Shapir, Y.: Sociophysics: a new approach of sociological collective behavior. J. Math. Sociol. 9, 1–13 (2009)
Hegselmann, R., Krause, U.: Opinion dynamics and bounded confidence models, analysis, and simulation. J. Artif. Soc. Soc. Simul. 5(3), 1–33 (2002)
Mäs, M., Flache, A.: Differentiation without distancing. explaining bi-polarization of opinions without negative influence. PLOS One 8(11), 1–17 (2013)
Mäs, M., Flache, A., Helbing, D.: Individualisazion as driving force of clustering phenomena in humans. PLOS One 6(10), 1–8 (2010)
Monica, S., Bergenti, F.: A stochastic model of self-stabilizing cellular automata for consensus formation. In: Proceedings of the 15th Workshop Dagli Oggetti agli Agenti (WOA 2014). CEUR Workshop Proceedings, vol. 1260. RWTH Aachen (2014)
Monica, S., Bergenti, F.: A kinetic study of opinion dynamics in multi-agent systems. In: Gavanelli, M., Lamma, E., Riguzzi, F. (eds.) AI*IA 2015. LNCS, vol. 9336, pp. 116–127. Springer, Cham (2015). doi:10.1007/978-3-319-24309-2_9
Monica, S., Bergenti, F.: Kinetic description of opinion evolution in multi-agent systems: analytic model and simulations. In: Chen, Q., Torroni, P., Villata, S., Hsu, J., Omicini, A. (eds.) PRIMA 2015. LNCS (LNAI), vol. 9387, pp. 483–491. Springer, Cham (2015). doi:10.1007/978-3-319-25524-8_30
Monica, S., Bergenti, F.: Simulations of opinion formation in multi-agent systems using kinetic theory. In: Proceedings of 16th Workshop “Dagli Oggetti agli Agenti” (WOA 2015). CEUR Workshop Proceedings, vol. 1382, pp. 97–102. RWTH Aachen (2015)
Monica, S., Bergenti, F.: An analytic study of opinion dynamics in multi-agent systems with additive random noise. In: Adorni, G., Cagnoni, S., Gori, M., Maratea, M. (eds.) AI*IA 2016. LNCS, vol. 10037, pp. 105–117. Springer, Cham (2016). doi:10.1007/978-3-319-49130-1_9
Monica, S., Bergenti, F.: Opinion dynamics in multi-agent systems: selected analytic models and verifying simulations. Comput. Math. Organ. Theory, 1–28 (2016). doi:10.1007/s10588-016-9235-z
Monica, S., Bergenti, F.: A study of consensus formation using kinetic theory. In: Proceedings of the 13th International Conference on Distributed Computing and Artificial Intelligence (DCAI 2016), pp. 213–221. Sevilla, Spain, June 2016
Monica, S., Bergenti, F.: An analytic study of opinion dynamics in multi-agent systems. Comput. Math. Appl. 73(10), 2272–2284 (2017)
Nowak, A., Szamrej, J., Latan, B.: From private attitude to public opinion: a dynamic theory of social impact. Psycol. Rev. 97, 362–376 (1990)
Pareschi, L., Toscani, G.: Interacting Multiagent Systems: Kinetic Equations and Montecarlo Methods. Oxford University Press, Oxford (2013)
Toscani, G.: Kinetic models of opinion formation. Commun. Math. Sci. 4, 481–496 (2006)
Yildiz, E., Ozdaglar, A., Acemoglu, D., Saberi, A., Scaglione, A.: Noisy continuous opinion dynamics. J. Stat. Mech. 9, 1–13 (1982)
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Monica, S., Bergenti, F. (2017). Two Analytic Models of Compromise in Multi-Agent Systems. In: Berndt, J., Petta, P., Unland, R. (eds) Multiagent System Technologies. MATES 2017. Lecture Notes in Computer Science(), vol 10413. Springer, Cham. https://doi.org/10.1007/978-3-319-64798-2_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-64798-2_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-64797-5
Online ISBN: 978-3-319-64798-2
eBook Packages: Computer ScienceComputer Science (R0)