Discontinuity, Nonlinearity, and Complexity
Who Replaces Whom? Local versus Non-local Replacement in Social and Evolutionary Dynamics
Discontinuity, Nonlinearity, and Complexity 2(1) (2012) 57--73 | DOI:10.5890/DNC.2012.12.002
Sven Banisch$^{1}$; Tanya Araújo$^{2}$
$^{1}$ Mathematical Physics, Bielefeld University, Germany
$^{2}$ ISEG - Technical University of Lisbon (TULisbon) and Research Unit on Complexity in Economics(UECE), Portugal
Download Full Text PDF
Abstract
In this paper, we inspect well–known population genetics and social dynamics models. In these models, interacting individuals, while participating in a self-organizing process, give rise to the emergence of complex behaviors and patterns. While one main focus in population genetics is on the adaptive behavior of a population, social dynamics is more often concerned with the splitting of a connected array of individuals into a state of global polarization, that is, the emergence of speciation. Applying computational and mathematical tools we show that the way the mechanisms of selection, interaction and replacement are constrained and combined in the modeling have an important bearing on both adaptation and the emergence of speciation. Differently (un)constraining the mechanism of individual replacement provides the conditions required for either speciation or adaptation, since these features appear as two opposing phenomena, not achieved by one and the same model. Even though natural selection, operating as an external, environmental mechanism, is neither necessary nor sufficient for the creation of speciation, our modeling exercises highlight the important role played by natural selection in the interplay of the evolutionary and the self–organization modeling methodologies.
Acknowledgments
Financial support of the German Federal Ministry of Education and Research (BMBF) through the project Linguistic Networks is gratefully acknowledged (http://project.linguistic-networks.net). This work has also benefited from financial support from the Fundação para a Ciência e a Tecnologia (FCT), under the 13 Multi-annual Funding Project of UECE, ISEG, Technical University of Lisbon.
References
-
[1]  | Araújo, T. and Vilela Mendes, R. (2009), Innovation and self-organization in a multi-agents model, Advances in Complex Systems, 12, 233-253. |
-
[2]  | Dobzhansky, T. (1970), Genetics of the Evolutionary Process, Columbia University Press, New York. |
-
[3]  | Castellano, C., Fortunato, S., and Loreto, V. (2009), Statistical physics of social dynamics, Reviews of Modern Physics, 81 (2), 591-646. |
-
[4]  | Huberman, B. A. and Glance, N. S. (1993), Evolutionary games and computer simulations, Proceedings of the National Academy of Sciences, 90(16), 7716-7718. |
-
[5]  | Banisch, S. (2010), Unfreezing social dynamics: Synchronous update and dissimilation, In: Ernst, A. and Kuhn, S., editors, Proceedings of the 3rd World Congress on Social Simulation 2010,WCSS2010. |
-
[6]  | Kehoe, T. J. and Levine, D. K. (1984), Regularity in overlapping generations exchange economies, Journal of Mathematical Economics, 13, 69-93. |
-
[7]  | Kauffman, S. A. (1993), The Origins of Order: Self-Organization and Selection in Evolution, Oxford University Press, USA. |
-
[8]  | Fisher, R. A. (1958), The Genetical Theory of Natural Selection, Dover Publications, New York, 2 edition. |
-
[9]  | Wright, S. (1932), The roles of mutation, inbreeding, crossbreeding, and selection in evolution, Proceedings of the Sixth International Congress on Genetics. |
-
[10]  | Crow, F. and Kimura, M. (1970), An introduction to population genetics theory, New York, Harper and Row. |
-
[11]  | Drossel, B. (2001), Biological evolution and statistical physics, Advances in Physics , 50, 209-295. |
-
[12]  | Smith, J.M. (1966), Sympatric speciation, The American Naturalist, 100(916), 637-650. |
-
[13]  | Kondrashov, A.S. and Shpak, M. (1998), On the origin of species by means of assortative mating, Proc. R. Soc. Lond. B, 265, 2273-2278. |
-
[14]  | Dieckmann, U. and Doebeli, M. (1999), On the origin of species by sympatric speciation, Nature, 400 (6742), 354-357. |
-
[15]  | Axelrod, R. (1997), The dissemination of culture: A model with local convergence and global polarization, The Journal of Conflict Resolution, 41(2), 203-226. |
-
[16]  | Deffuant, G., Neau, D., Amblard, F., andWeisbuch, G. (2001), Mixing beliefs among interacting agents, Advances in Complex Systems, 3, 87-98. |
-
[17]  | Moran, P.A.P. (1958), Random processes in genetics, In: Proceedings of the Cambridge Philosophical Society, 54, 60-71. |
-
[18]  | Korolev, K.S., Avlund, M., Hallatschek, O., and Nelson, D.R. (2010), Genetic demixing and evolution in linear stepping stone models, Reviews of Modern Physics, 82, 1691-1718. |
-
[19]  | Banisch, S., Lima, R., and Araújo, T. (2012), Agent Based Models and Opinion Dynamics as Markov Chains, Social Networks, 34, 549-561. |
-
[20]  | Banisch, S., and Lima, R. (2012), Markov Projections of the Voter Model, Forthcoming, (http://arxiv.org/abs/1108.1716). |
-
[21]  | Seneta, E. (2006), Non-negativeMatrices andMarkov Chains (Springer Series in Statistics), Springer, 2nd edition. |