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Cities and methods from complexity science

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Abstract

The dynamics of human society is now been studying in the context of the artificial environment created by cities. In this work, the authors describe some of the formal methods used in complexity science to study urban systems. The authors discuss some of the important quantitative approaches on cities paying attention to some of the deepest controversies in present scientific studies. The authors will stress the importance of a transdisciplinary approach when studying this type of cooperative social environments.

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References

  1. United Nations Department of Economic and Social Affairs. World Population to 2300, Executive Summary, 2004.

  2. Sjoberg G, The origin and evolution of cities, Scientific American, 1965, 3: 3–54.

    Google Scholar 

  3. Bairoch P, Cities and Economic Development: From the Dawn of History to the Present, University of Chicago Press, 1988.

    Google Scholar 

  4. Fujita M and Mori T, Structural stability and evolution of urban systems, Regional Science and Urban Economics, 1997, 27(4): 399–442.

    Article  Google Scholar 

  5. Brockman J, Third Culture: Beyond the Scientific Revolution, Simon and Schuster, 1996.

    Google Scholar 

  6. Bettencourt L M, Lobo J, Helbing D, et al., Growth, innovation, scaling, and the pace of life in cities, Proceedings of the National Academy of Sciences, 2007, 104(17): 7301–7306.

    Article  Google Scholar 

  7. Boccara N, Modeling Complex Systems, Springer-Verlag, New York, 2004.

    MATH  Google Scholar 

  8. Erdi P, Complexity Explained, Springer-Verlag, Berlin Heidelberg, 2008.

    MATH  Google Scholar 

  9. Mitchell M, Complexity a Guided Tour, Oxford University Press, 2009.

    MATH  Google Scholar 

  10. Miller J H and Page S E, Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton Studies in Complexity, 2007.

    MATH  Google Scholar 

  11. Nicolis G and Nicolis C, Foundations of Complex Systems, Nonlinear Dynamics, Statistical Physics, Information and Prediction, 2007.

    MATH  Google Scholar 

  12. Bedau M A and Humphreys P, Emergence: Contemporary Readings in Philosophy and Science, The MIT Press, 2008.

    Book  Google Scholar 

  13. Nicolis G, Introduction to Nonlinear Science, Cambridge University Press, 1995.

    Book  Google Scholar 

  14. Strogatz S H, Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering, Studies in Nonlinearity. Westview Press, First Edition, 2001.

    Google Scholar 

  15. Jacobs J, The Death and Life of Great American Cities, Modern Library, New York: Random House, February (new ed. 1993), ISBN 0-679-60047-7, 1961.

    Google Scholar 

  16. Lobo J, Bettencourt L M A, Strumsky D, et al., Urban scaling and the production function for cities, PLoS ONE, 2013, 8(3): e58407. doi:10.1371/ journal.pone.0058407.

    Article  Google Scholar 

  17. Ottaviano G I and Peri G, The economic value of cultural diversity: Evidence from US cities, Journal of Economic Geography, 2006, 6(1): 9–44.

    Article  Google Scholar 

  18. Amin A and Parkinson M, Ethnicity and the multicultural city: Living with diversity, Environment and planning A, 2002, 34(6): 959–980.

    Article  Google Scholar 

  19. Van Criekingen M and Decroly J M, Revisiting the diversity of gentrification: Neighbourhood renewal processes in Brussels and Montreal, Urban Studies, 2003, 40(12): 2451–2468.

    Article  Google Scholar 

  20. Tainter J, The Collapse of Complex Societies, Cambridge University Press, 1990.

    Google Scholar 

  21. Domb C, The Critical Point, Taylor & Francis, 1996.

    Google Scholar 

  22. Guckenheimer J and Holmes P, Nonlinear Oscillations, Dynamical Systems and Bifurcations of Vector Fields, Applied Mathematical Sciences, Springer; 1st ed. 1983. Corr. 6th Edition, 2002.

    MATH  Google Scholar 

  23. Turing A M, The chemical basis of morphogenesis, Philosophical Transactions of the Royal Society of London B: Biological Sciences, 1952, 237(641): 37–72.

    Article  MathSciNet  Google Scholar 

  24. Murray J D, Mathematical Biology: An Introduction, 3rd Edition, Volume I and II, Interdisciplinary Applied Mathematics, Springer, 2007.

    Google Scholar 

  25. Lim M, Metzler R, and Bar-Yam Y, Global pattern formation and ethnic/cultural violence, Science, 2007, 317(5844): 1540.

    Article  Google Scholar 

  26. Costa L D F, Rodrigues F A, Travieso G, et al., Characterization of complex networks: A survey of measurements, Advances in Physics, 2007, 56(1): 167–242.

    Article  Google Scholar 

  27. Newman M, Barabasi A, and Watts D J, The Structure and Dynamics of Networks, Princeton Studies in Complexity, Princeton University Press, 2006.

    Google Scholar 

  28. Frank A B, Collins M G, Levin S A, et al., Dealing with femtorisks in international relations, Proceedings of the National Academy of Sciences, 2014, 111(49): 17356–17362.

    Article  Google Scholar 

  29. Moore C and Newman M E, Epidemics and percolation in small-world networks, Physical Review E, 2000, 61(5): 5678–5682.

    Article  Google Scholar 

  30. Von Neumann J and Morgenstern O, Theory of games and economic behavior, 60th Anniversary Commemorative Edition, Princeton University Press, 2007.

    MATH  Google Scholar 

  31. Shannon C E, A mathematical theory of communication, Bell System Technical Journal, 1948, 27(3): 379–423.

    Article  MathSciNet  MATH  Google Scholar 

  32. Rosenkrantz R D and Jaynes E T, Papers on Probability, Statistics and Statistical Physics, Synthese Library, Springer, 1989.

  33. Gell-Mann M and Lloyd S, Information measures, effective complexity, and total information, Complexity, 1996, 2(1): 44–52.

    MathSciNet  MATH  Google Scholar 

  34. Batty M, Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals, The MIT Press, 2007.

  35. Bonabeau E, Agent-based modeling: Methods and techniques for simulating human systems, Proceedings of the National Academy of Sciences of the United States of America, National Academy of Sciences. May 14, 2002.

    Google Scholar 

  36. Kantardzic M, Data Mining: Concepts, Models, Methods, and Algorithms, John Wiley & Sons, ISBN 0-471-22852-4. OCLC 50055336, 2003.

    MATH  Google Scholar 

  37. Muhammad A, Ferreira J, and Fonseca J, Introduction to Intelligent Transportation Systems, Intelligent Transportation Systems, Springer International Publishing, 2016.

    Google Scholar 

  38. Whitmore A, Anurag A, and Li D X, The Internet of things: A survey of topics and trends, Information Systems Frontiers, 2015, 17(2): 261–274.

    Article  Google Scholar 

  39. Portugali J, Meyer H, Stolk E, et al., Complexity Theories of Cities Have Come of Age: An Overview with Implications to Urban Planning and Design, Springer Science & Business Media, 2012.

    Book  Google Scholar 

  40. Kleiber M, Body size and metabolic rate, Physiol. Rev., 1947, 27: 27–511.

    Google Scholar 

  41. West G B, Brown J H, and Enquist B J, A general model for the origin of allometric scaling laws in biology, Science, 1997, 276: 276–122.

    Article  Google Scholar 

  42. Bettencourt L and West G, A unified theory of urban living, Nature, 2010, 467(7318): 912–913.

    Article  Google Scholar 

  43. Arcaute E, Hatna E, Ferguson P, et al., Constructing cities, deconstructing scaling laws, J. R. Soc. Interface, 2015, 12: 20140745. http://dx.doi.org/10.1098/rsif.2014.0745.

    Article  Google Scholar 

  44. Rmi L and Barthelemy M, Scaling: Lost in the smog, arXiv preprint, arXiv:1410.4964, 2014.

    Google Scholar 

  45. United Nations, World Heritage 38 COM, Paris, 30 April, 2014, 69.

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Author information

Authors and Affiliations

  1. CIDES Corpotraining, Av. Providencia 2370, Santiago, Chile

    Beatriz Balmaceda

  2. Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico, 87501, USA

    Miguel Fuentes

  3. IIF-Sadaf/CONICET, Bulnes 642, Buenos Aires, 1176, Argentina

    Miguel Fuentes

  4. Facultad de Ingeniería y Tecnología, Universidad San Sebastián, Lota 2465, Santiago, 7510157, Chile

    Miguel Fuentes

Authors
  1. Beatriz Balmaceda
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  2. Miguel Fuentes
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Corresponding author

Correspondence to Beatriz Balmaceda.

Additional information

This paper was recommended for publication by Editor-in-Chief GAO Xiao-Shan.

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Balmaceda, B., Fuentes, M. Cities and methods from complexity science. J Syst Sci Complex 29, 1177–1186 (2016). https://doi.org/10.1007/s11424-016-6084-2

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  • DOI: https://doi.org/10.1007/s11424-016-6084-2

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