[Vers une mécanique statistique des villes]
Les villes sont parmi les systèmes dynamiques les plus complexes des sociétés humaines et de la nature. On s'intéresse de plus en plus à la production d'une théorie quantitative plus complète, capable de décrire bon nombre de caractéristiques maintenant observables en milieu urbain, en particulier celles qui montrent des régularités empiriques dans des villes de tailles, de géographies et de niveaux de développement différents. Le principal défi pour atteindre un tel objectif est notre capacité à construire des cadres qui incluent des comptes rendus réalistes, mais simples, des choix et du comportement stratégique des agents, au-delà des approches actuelles en physique statistique ou en économie. Je propose ici un cadre général qui intègre le comportement des agents avec leur gestion des ressources et de l'information pour saisir les opportunités dans leur environnement. Je montre comment cette approche intègre la théorie de l'échelle urbaine à une mécanique statistique de la croissance (économique) ouverte. Le cadre est général et, avec des modifications et des précisions appropriées, il peut tenir compte de la dynamique statistique d'autres systèmes complexes.
Cities are some of the most complex dynamical systems in human societies and in nature. There is growing interest in producing more comprehensive quantitative theory, capable of describing many of the features now observable in urban environments, especially those that show empirical regularities across cities of different sizes, geographies, and levels of development. The principal challenge of achieving such a goal is our ability to build frameworks that include realistic but simple accounts of agents' choices and strategic behavior, beyond current approaches in statistical physics or economics. Here, I propose a general framework that integrates agents' behavior with their resource and information management towards seizing opportunities in their environment. I show how this approach integrates urban scaling theory with a statistical mechanics of open-ended (economic) growth. The framework is general and, with appropriate modifications and elaborations, can account for the statistical dynamics of other complex systems.
Mot clés : Information, Croissance multiplicative, Réseaux, Renormalisation, Lois d'échelle, Urbanisation
Luís M.A. Bettencourt 1, 2, 3
@article{CRPHYS_2019__20_4_308_0,
author = {Lu{\'\i}s M.A. Bettencourt},
title = {Towards a statistical mechanics of cities},
journal = {Comptes Rendus. Physique},
pages = {308--318},
publisher = {Elsevier},
volume = {20},
number = {4},
year = {2019},
doi = {10.1016/j.crhy.2019.05.007},
language = {en},
}
Luís M.A. Bettencourt. Towards a statistical mechanics of cities. Comptes Rendus. Physique, Volume 20 (2019) no. 4, pp. 308-318. doi : 10.1016/j.crhy.2019.05.007. https://comptes-rendus.academie-sciences.fr/physique/articles/10.1016/j.crhy.2019.05.007/
[1] Advances in Urban Ecology: Integrating Humans and Ecological Processes in Urban Ecosystems, Springer, New York, 2008
[2] The Evolution of Great World Cities: Urban Wealth and Economic Growth, University of Toronto Press, Toronto, Buffalo, 2011
[3] Growth, innovation, scaling, and the pace of life in cities, Proc. Natl. Acad. Sci. USA, Volume 104 (2007) no. 17, pp. 7301-7306 | DOI
[4] An evolutionary theory for interpreting urban scaling laws, Cybergeo (2006) | DOI
[5] The size, scale, and shape of cities, Science, Volume 319 (2008) no. 5864, pp. 769-771 | DOI
[6] The origins of scaling in cities, Science, Volume 340 (2013) no. 6139, pp. 1438-1441 | DOI
[7] The statistics of urban scaling and their connection to Zipf's law, PLoS ONE, Volume 7 (2012) no. 7 | DOI
[8] The City, University of Chicago Press, 1984
[9] Location and Land Use: Toward a General Theory of Land Rent, Harvard Univ. Press, Cambridge, MA, USA, 1977
[10] Cities, Agglomeration, and Spatial Equilibrium, Oxford University Press, Oxford, UK, 2008
[11] Settlement scaling and increasing returns in an ancient society, Sci. Adv., Volume 1 (2015) no. 1 | DOI
[12] A systematic method for estimating the populations of Greek and Roman settlements, J. Roman Archaeol., Volume 30 (2017), pp. 301-324 | DOI
[13] Heterogeneity and scale of sustainable development in cities, Proc. Natl. Acad. Sci. USA, Volume 114 (2017) no. 34, pp. 8963-8968 | DOI
[14] Urban scaling in Europe, J. R. Soc. Interface, Volume 13 (2016) no. 116 | DOI
[15] Urban geography and scaling of contemporary Indian cities, J. R. Soc. Interface, Volume 16 (2019) no. 152 | DOI
[16] Urban Growth and the Emergence Statistics of Cities, Mansueto Institute, 2018 (Working Paper)
[17] Economic Growth, The MIT Press, Cambridge, MA, USA, 2003
[18] The new Kaldor facts: ideas, institutions, population, and human capital, Am. Econ. J. Macroecon., Volume 2 (2010) no. 1, pp. 224-245 | DOI
[19] On the mechanics of economic development, J. Monet. Econ., Volume 22 (1988) no. 1, pp. 3-42 | DOI
[20] Non-Equilibrium Social Science and Policy: Introduction and Essays on New and Changing Paradigms in Socio-Economic Thinking, Springer, Berlin, Heidelberg, New York, 2016
[21] Statistical Mechanics, World Scientific, Philadelphia, PA, USA, 1985
[22] What Is Life? The Physical Aspect of the Living Cell, Cambridge University Press, Cambridge, New York, 1992
[23] Phase Transitions and Renormalization Group, Oxford University Press, Oxford, New York, 2007
[24] Cities as organisms: allometric scaling of urban road networks, J. Transp. Land Use, Volume 1 (2008) no. 1, pp. 21-39 | DOI
[25] Wealth condensation in a simple model of economy, Physica A, Volume 282 (2000) no. 3–4, pp. 536-545 | DOI
[26] Stochastic Processes: From Physics to Finance, Springer, Heidelberg, Germany, 2013
[27] Capital is back: wealth–income ratios in rich countries 1700–2010, Q. J. Econ., Volume 129 (2014) no. 3, pp. 1255-1310 | DOI
[28] Power laws of wealth, market order volumes and market returns, Physica A, Volume 299 (2001) no. 1–2, pp. 188-197 | DOI
[29] Natural selection. IV. The Price equation*, J. Evol. Biol., Volume 25 (2012) no. 6, pp. 1002-1019 | DOI
[30] Stochastic Volatility Modeling, CRC Press, Boca Raton, FL, USA, 2016
[31] A new interpretation of information rate, IRE Trans. Inf. Theory, Volume 2 (1956) no. 3, pp. 185-189 | DOI
[32] Information theory and statistics, Elements of Information Theory, Wiley, 2006
[33] Interpreting Prediction Market Prices as Probabilities, 2006 https://ssrn.com/abstract=898597
[34] The rules of information aggregation and emergence of collective intelligent behavior, Top. Cogn. Sci., Volume 1 (2009) no. 4, pp. 598-620 | DOI
[35] The more you know, the more you can grow: an information theoretic approach to growth in the information age, Entropy, Volume 19 (2017) no. 2, p. 82 | DOI
[36] Professional diversity and the productivity of cities, Sci. Rep., Volume 4 (2014), p. 5393 | DOI
[37] Impact of changing technology on the evolution of complex informational networks, Proc. IEEE, Volume 102 (2014) no. 12, pp. 1878-1891 | DOI
[38] Income inequality, race, and place: does the distribution of race and class within neighborhoods affect crime rates?, Criminology, Volume 45 (2007) no. 3, pp. 665-697 | DOI
[39] Cities and Regions as Self-organizing Systems: Models of Complexity, Vol. 1, Gordon and Breach, Luxembourg, 1997
Cité par Sources :
Commentaires - Politique