Abstract
There are growing interests for studying collective behavior including the dynamics of markets, the emergence of social norms and conventions, and collective phenomena in daily life such as traffic congestion.
We showed that collective behavior is affected in the structure of the social net-work and theta, and the collective behavior was stochastic in previous work. Moreover, collective behavior is almost same as Schelling model, though the decision is not interactive and simultaneously. Then, we found that the collective behavior in Schelling model is similar to cascade model. That is, our results with heterogeneous rules or heterogeneous networks are possible to apply for cascade model. In this paper, we analyzed that the collective behavior of population is stochastic, although decisions of agents are deterministic. We focused on the effect of network degree. And we found that turn of decision is effect on collective behavior not the first choices.
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
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Huberman, B.A., Glance, N.S.: Diversity and Collective Action. Interdisciplinary Approaches to Nonlinear Complex Systems. Springer Series in Synergetics, vol. 62, pp. 44–64 (1993)
Sipper, M.: Evolution of Parallel Cellular Machines: The Cellular Programming Approach. Springer, Heidelberg (1997)
Schweitzer, F.: Brownian agent models for swarm and chemotactic interaction. In: Fifth German Workshop on Artificial Life. Abstracting and Synthesizing the Principles of Living Systems, pp. 181–190 (2002)
Kirman, A.P.: The Economy as an Interactive System. In: Arthur, W.B., Durlauf, S.N., Lane, D. (eds.) The Economy as an Evolving Complex System II, Perseus (1997)
Feng, L., Li, B., Podobnik, B., Preis, T., Stanley, H.E.: Linking agent-based models and stochastic models of financial markets. National Academy of Sciences of the United States of America (PNAS) 109(2), 8388–8393 (2012)
Kenett, D.Y., Raddant, M., Lux, T., Ben-Jacob, E.: Evolvement of Uniformity and Volatility in the Stressed Global Financial Village. PLoS One 7(2), e31144 (2012)
Schelling, T.: Micromotives and Macrobehavior, Norton (1978)
Arthur, W.B.: Inductive reasoning and bounded rationality. American Economic Review 84, 406–411 (1994)
Hansarnyi, J., Selten, R.: A Game Theory of Equilibrium Selection in Games. MIT Press (1988)
Fudenberg, D., Levine, D.: The Theory of Learning in Games. The MIT Press (1998)
Rubinstein, A.: Modeling Bounded Rationality. The MIT Press (1998)
Arthur, W.B.: Competing Technologies, Increasing Returns, and Lock-In by Historical Events. The Economic Journal 99(394), 116–131 (1989)
Morris, S.: Contagion. Review of Economic Studies 67(1), 57–78 (2000)
López-Pintado, D.: Contagion and coordination in random networks. International Journal of Game Theory 34(3), 371–381 (2006)
Watts, D.J.: A simple model of global cascades on random networks. National Academy of Sciences of the United States of America (PNAS) 99(9), 5766–5771 (2002)
Young, H.P.: The dynamics of social innovation. National Academy of Sciences of the United States of America (PNAS) 108(4), 21285–21291 (2011)
Montanari, A., Saberi, A.: The spread of innovation in social networks. National Academy of Sciences of the United States of America (PNAS) 107(47), 20196–20201 (2010)
Komatsu, T., Namatame, A.: Evolutionary optimized network topology for maximizing cascade. In: The Special Interest Group Technical Reports of Processing Society of Japan (IPSJ SIG Technical Report), 20120ICS-166(3), 1–6 (2012)
Nowak, M.A.: Evolutionary Dynamics: Exploring the Equations of Life. Belknap Press of Harvard University Press (2006)
Axelrod, R.: The Evolution of Cooperation. Basic Books (1985)
Albert, R., Barabási, A.L.: Topology of evolving networks: Local events and universality. Physical Review Letters 85(24), 5234–5237 (2000)
Watts, D.J.: Small-Worlds: The Dynamics of Networks between Order and Randomness. Princeton University Press (1999)
Hasan, S., Ukkusuri, S.V.: A threshold model of social contagion process for evacuation decision making. Transportation Research Part B: Methodological 45(10), 1590–1605 (2011)
Iwanaga, S., Namatame, A.: Collective behavior and diverse social network. International Journal of Advancements in Computing Technology 4(22), 320–321 (2012)
Iwanaga, S., Namatame, A.: Collective Behavior in Cascade and Schelling Model. In: 17th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2013), vol. 24, pp. 217–226 (2013); Procedia Computer Science
Kawachi, Y., Murata, K., Yoshii, S., Kakazu, Y.: The structural phase transition among fixed cardinal networks. In: the 7th Asia-Pacific Conference on Complex Systems, pp. 247–255 (2004)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Iwanaga, S., Namatame, A. (2015). Collective Behavior in Cascade Model Depend on Turn of Choice. In: Handa, H., Ishibuchi, H., Ong, YS., Tan, K. (eds) Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, Volume 1. Proceedings in Adaptation, Learning and Optimization, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-13359-1_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-13359-1_3
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13358-4
Online ISBN: 978-3-319-13359-1
eBook Packages: EngineeringEngineering (R0)