From social simulation to integrative system design

Abstract.

The purpose of this White Paper of the EU Support Action “Visioneer” (see www.visioneer.ethz.ch) is to address the following goals:

  1. 1.

    Develop strategies to build up social simulation capacities.

  2. 2.

    Suggest ways to build up an “artificial societies” community that aims at simulating real and alternative societies by means of supercomputers, grid or cloud computing.

  3. 3.

    Derive proposals to establish centers for integrative systems design.

References

  1. 1.

    D. Helbing, S. Balietti, Fundamental and real world challenges in economics (print) (2010)

  2. 2.

    D. Helbing, S. Balietti, Formulating grand fundamental challenges, http://www.visioneer.ethz.ch

  3. 3.

    D. Helbing, S. Balietti, How to create an Innovation Accelerator. , Eur. Phys. J. Special Topics 195, 101 (2011)http://www.visioneer.ethz.ch

    Article  ADS  Google Scholar 

  4. 4.

    D. Helbing, S. Balietti, From Social Data Mining to Forecasting Socio-Economic Crises Eur. Phys. J. Special Topics 195, 3 (2011)http://www.visioneer.ethz.ch

    Article  ADS  Google Scholar 

  5. 5.

    D. Helbing, Pluralistic modeling of complex systems, CCSS-10-009 (2010), http://ssrn.com/abstract=1646314(2010)

  6. 6.

    R.E. Shannon, In WSC ’98: Proceedings of the 30th conference on Winter simulation (Los Alamitos, CA, USA, 1998) (IEEE Computer Society Press), pp. 7–14

  7. 7.

    G.H. Orcutt, Rev. Econ. Stat. 58, 773 (1957)

    Google Scholar 

  8. 8.

    N. Gilbert, K.G. Troitzsch, Simulation for the Social Scientist (Open University Press, 2005)

  9. 9.

    S. Weinberg, New York Rev. Books 49, 16 (2002)

    Google Scholar 

  10. 10.

    S. Wolfram, A New Kind of Science, English (Wolfram Media, 2002), http://www.wolframscience.com

  11. 11.

    I. Foster, Nature 440, 419 (2006)

    ADS  Article  Google Scholar 

  12. 12.

    C.S. Taber, R.J Timpone, Comput. Model. Sage, 1996

  13. 13.

    H.J. Aaron, J. Econom. Perspect. 8, 3 (1994), http://ideas.repec.org/a/aea/jecper/v8y1994i2p3-21.html

    Article  Google Scholar 

  14. 14.

    A.P. Kirman, J. Econom. Perspect. 6, 117 (1992), http://ideas.repec.org/a/aea/jecper/v6y1992i2p117-36.html

    Google Scholar 

  15. 15.

    D. Helbing, Managing Complexity: Insights, Concepts, Applications, 1st edn. (Springer, 2007)

  16. 16.

    D. Helbing, Systemic risks in society and economics, Sante Fe Institute, working paper 09-12-044 (2009), http://www.santafe.edu/research/working-papers/abstract/9596e5a57d1f9b7e8fcc289f118555ce/

  17. 17.

    H.V.D. Parunak, Ann. Opera. Res. 75, 69 (1997)

    MATH  Article  Google Scholar 

  18. 18.

    Earth simulator: UK-japan climate collaboration, http://www.earthsimulator.org.uk/

  19. 19.

    K. Nagel, Parall. Comput. 27, 1611 (2001)

    MATH  Article  Google Scholar 

  20. 20.

    M. Rickert, NagelK, Future Gener. Comput. Syst. 17, 637 (2001)

    Article  Google Scholar 

  21. 21.

    K. Nagel, R.J. Beckman, C.L. Barrett, Transims for urban planning, LA-UR-98-4389 (1999)

  22. 22.

    K. Nagel, C.L. Barrett, Using microsimulation feedback for trip adaptation for realistic traffic in dallas (1997)

  23. 23.

    P.M. Simon, J. Esser, K. Nagel, Int. J. Modern Physics C 10, 941 (1999)

    ADS  Article  Google Scholar 

  24. 24.

    B. Raney, N. Cetin, A. Vollmy, M. Vrtic, K. Axhausen, K. Nagel, Networks Spatial Econom. 3, 23 (2003)

    Article  Google Scholar 

  25. 25.

    M. Balmer, K.W. Axhausen, K. Nagel, An agent based demand modeling framework for large scale micro-simulations (ETH Zurich, Switzerland 2005)

  26. 26.

    D. Charypar, K. Nagel, Transportation 32, 369 (2005)

    Article  Google Scholar 

  27. 27.

    K.W. Axhausen, T. Garling, Transport Rev. 12, 323 (1992)

    Article  Google Scholar 

  28. 28.

    D. Helbing, K. Nagel, Contemp. Phys. 45, 405 (2004)

    ADS  Article  Google Scholar 

  29. 29.

    V. Killer, et al., 50th European Regional Science Association (ERSA) (Sweden, 2010)

  30. 30.

    G. Laemmel, D. Grether, K. Nagel, Transportation Research Part C: Emerging Technologies (2009)

  31. 31.

    H. Taubenboeck, et al., Natur. Haz. Earth Syst. Sci. 9, 1509 (2009)

    ADS  Article  Google Scholar 

  32. 32.

    J. Min, et al., IIE Trans. 39, 57 (2007)

    MathSciNet  Article  Google Scholar 

  33. 33.

    C. Barrett, S. Eubank, M. Marathe, Interactive Computation, edited by D. Goldin, S.A. Smolka, P. Wegner (Springer, Berlin, Heidelberg, 2006), pp. 353–392

  34. 34.

    National infrastructure simulation and analysis center (NISAC), http://www.lanl.gov/programs/nisac/

  35. 35.

    W. Kermack, A. Mckendrick, Bull. Math. Biol. 53, 33 (1991)

    Google Scholar 

  36. 36.

    W. Kermack, A. Mckendrick, Bull. Math. Biol. 53, 57 (1991)

    Google Scholar 

  37. 37.

    W. Kermack, A. McKendrick, Bull. Math. Biol. 53, 89 (1991)

    Google Scholar 

  38. 38.

    V. Colizza, A. Barrat, M. Bartholemy, A. Vespignani, Proc. Nation. Acad. Sci. USA 103, 2015 (2006)

    ADS  Article  Google Scholar 

  39. 39.

    J.M. Epstein, Nature 460, 687 (2009)

    ADS  Article  Google Scholar 

  40. 40.

    L. Hufnagel, D. Brockmann, T. Geisel, Proc. Nation. Acad. Sci. USA 101, 15124 (2004), http://www.pnas.org/content/101/42/15124.full.pdf+html, http://www.pnas.org/content/101/42/15124.abstract

    ADS  Article  Google Scholar 

  41. 41.

    S. Eubank, et al., Nature 429, 180 (2004)

    ADS  Article  Google Scholar 

  42. 42.

    Artificial stock market, http://sourceforge.net/projects/artstkmkt/

  43. 43.

    U-mart, http://www.u-mart.org/

  44. 44.

    Eurace, http://www.eurace.org/

  45. 45.

    D. Helbing, W. Yu, Proc. Nation. Acad. Sci. 106, 3680 (2009)

    ADS  Article  Google Scholar 

  46. 46.

    D. Helbing, A. Johansson, Cooperation, norms, and conflict: A unified approach. SFI Working Paper (2009)

  47. 47.

    D. Helbing, et al., PLoS Comput Biol. 6, e1000758 (2010)

    MathSciNet  Article  Google Scholar 

  48. 48.

    A. Cangelosi, D. Parisi, Simulating the evolution of language (Springer-Verlag, 2002)

  49. 49.

    R. Dunbar, Grooming, gossip, and the evolution of language (Harvard Univ Pr, 1998)

  50. 50.

    M.A. Nowak, D.C. Krakauer, Proc. Nation. Acad. Sci. USA 96, 8028 (1999)

    ADS  Article  Google Scholar 

  51. 51.

    J.M. Epstein, R. Axtell, Growing artificial societies (Cambridge, MA, 1996)

  52. 52.

    Parallel discrete-event simulation of population dynamics (2008), pp. 1047–1054

  53. 53.

    Prace: Partnership for advanced computing in europe, http://www.prace-project.eu/

  54. 54.

    D. Helbing, H. Ammoser, C. Kuehnert, Chap. Disasters as extreme events and the importance of network interactions for disaster response management, edited by S. Albeverio, V. Jentsch, H. Kantz (Berlin: Springer, 2005), pp. 319–348

  55. 55.

    J. Sterman, Business dynamics: systems thinking and modeling for a complex world (Irwin, McGraw-Hill, 2000)

  56. 56.

    Transims: Transportation analysis and simulation system, http://www.transims-opensource.net/

  57. 57.

    Matsims: Multi-agent transport simulation toolkit, http://www.matsim.org/

  58. 58.

    Essa: European social simulation association, http://www.essa.eu.org/

  59. 59.

    D. Helbing, W. Yu, PNAS 12, 5265 (2010)

    ADS  Article  Google Scholar 

  60. 60.

    A. Tversky, D. Kahneman, Science 211, 453 (1981)

    MathSciNet  ADS  Article  MATH  Google Scholar 

  61. 61.

    Add-ons for firefox, https://addons.mozilla.org/en-US/firefox/

  62. 62.

    Drupal, an open source content management system. modules page, http://drupal.org/project/Modules

  63. 63.

    Apple web apps store, http://www.apple.com/webapps/

  64. 64.

    Google android market, http://www.android.com/market

  65. 65.

    Swarm, http://www.swarm.org/

  66. 66.

    Repast, recursive porous agent simulation toolkit, http://repast.sourceforge.net/

  67. 67.

    Netlogo, http://ccl.northwestern.edu/netlogo/

  68. 68.

    Sesam, shell for simulated agent systems, http://www.simsesam.de/

  69. 69.

    Wikipedia: Comparison of agent-based modeling software, http://en.wikipedia.org/wiki/Comparison_of_agent-based_modeling_software

  70. 70.

    Matlab, http://www.mathworks.com/

  71. 71.

    J.M. Epstein, J. Artific. Soc. Simul. 11, 12 (2008)

    Google Scholar 

  72. 72.

    S. Laemmer, D. Helbing, JSTAT, P04019 (2008)

  73. 73.

    D. Helbing, S. Laemmer, http://www.patent-de.com/20100805/DE102005023742B4.html 2010

  74. 74.

    D. Helbing, M. Christen, Mit rauschen und reibung gegen finanzielle blasen (submitted) (Wirtschaftswoche, 2010)

  75. 75.

    D. Helbing, A. Deutsch, S Diez, K Peters, Y Kalaidzidis, K. Padberg-Gehle, S. Laemmer, A. Johansson, G. Breier, F. Schulze, M. Zerial, Adv. Compl. Syst. 12, 533 (2009)

    Article  Google Scholar 

  76. 76.

    A. Kesting, M. Treiber, M. Schonhof, D. Helbing, Transport. Res. Part C: Emerg. Technol. 16, 668 (2008)

    Article  Google Scholar 

  77. 77.

    D. Helbing, Chap. Dynamic decision behavior and optimal guidance through information services: Models and experiments, edited by M. Schreckenberg, R. Selten (Springer, Berlin, 2004), pp. 47–95

  78. 78.

    N. Wiener, Cybernetics, Second Edition: or the Control and Communication in the Animal and the Machine (The MIT Press, 1965)

  79. 79.

    B. Fabien, Analytical System Dynamics: Modeling and Simulation (Springer, 2008)

  80. 80.

    S. Skogestad, I. Postlethwaite, Multivariable Feedback Control: Analysis and Design, 2nd edn. (Wiley-Interscience, 2005)

  81. 81.

    A.L. Fradkov, I.V. Miroshnik, V.O. Nikiforov, Nonlinear and Adaptive Control of Complex Systems (Springer, 1999)

  82. 82.

    J.H. Kagel, The Handbook of Experimental Economics (Princeton University Press, 2004)

  83. 83.

    N. Bardsley, R. Cubitt, G. Loomes, P. Moffatt, C. Starmer, R. Sugden, Experimental Economics: Rethinking the Rules (Princeton University Press, Princeton, NJ, 2009)

  84. 84.

    D. Friedman, A. Cassar, Economics Lab: An Intensive Course in Experimental Economics (London and New York: Routledge, 2004)

  85. 85.

    D. Friedman, S. Sunder, Experimental Methods: A Primer for Economists (Cambridge University Press, 1994)

  86. 86.

    F. Guala, The Methodology of Experimental Economics (Cambridge University Press, 2005), http://ideas.repec.org/b/cup/cbooks/9780521618618.html

  87. 87.

    M.J. Salganik, P.S. Dodds, D.J. Watts, Science 311, 854 (2006)

    ADS  Article  Google Scholar 

  88. 88.

    M. Szell, S. Thurner, Social Networks 32, 313 (2010)

    Article  Google Scholar 

  89. 89.

    W.S. Bainbridge, Science 317, 472 (2007)

    ADS  Article  Google Scholar 

  90. 90.

    N.F. Johnson, et al., Phys. Rev. E 79, 066117 (2009)

    ADS  Article  Google Scholar 

  91. 91.

    D.B. Fogel, Evolutionary computation 1: basic algorithms and operators (2000), p. 1

  92. 92.

    D.B. Fogel, Evolutionary computation: toward a new philosophy of machine intelligence (Wiley-IEEE Press, 2006)

  93. 93.

    S. Haykin, Neural networks: a comprehensive foundation (Prentice Hall PTR Upper Saddle River, NJ, USA, 1994)

  94. 94.

    M.T. Hagan, H.B Demuth, M. Beale, et al., Neural network design (PWS Pub, 1996)

  95. 95.

    C.A. Janeway, et al., Immunobiology: the immune system in health and disease (Churchill Livingstone, 2001)

  96. 96.

    R.M. May, Stability and Complexity in Model Ecosystems (Princeton Landmarks in Biology, Princeton University Press, 2001)

  97. 97.

    R. May, A. McLean, Theoretical Ecology: Principles and Applications, 3rd edn. (Oxford University Press, USA, 2007)

  98. 98.

    D. Helbing, M. Moussaid, Tech. Rep. [arXiv:0807.4006], Comments: For related work see http://www.soms.ethz.ch/ 2008

  99. 99.

    D. Helbing, Rev. Mod. Phys. 4, 1067 (2000) (cond-mat/0012229)

    MathSciNet  Google Scholar 

  100. 100.

    Why economists failed to predict the financial crisis, http://www.ftpress.com/articles/article.aspx?p=1350507

  101. 101.

    D. Keim, IEEE Trans. Visual. Comp. Graph. 8, 1 (2002)

    Article  Google Scholar 

  102. 102.

    A. Kageyama, N. Ohno, Proc. ISSS-7 (2005), p. 127

  103. 103.

    A. Jacobs, ACM Queue 7, 6 (2009)

    Article  Google Scholar 

  104. 104.

    B. Shneiderman, Visual Languages, IEEE Symposium on 0, 336 (1996)

    Article  Google Scholar 

  105. 105.

    R.M. Pickett, G.G. Grinstein, Proc. IEEE Conf. on Systems, Man and Cybernetics (Piscataway, NJ, 1988), pp. 514–519

  106. 106.

    H. Chernoff, J. Amer. Statistical Association 68, 361 (1973)

    Article  Google Scholar 

  107. 107.

    E.A. Bier, et al., Proc. SIGGRAPH, Anaheim (CA, 1993), p. 7380

  108. 108.

    A. Inselberg, B. Dimsdale, Proc. Visualization (San Francisco, CA, 1990), pp. 361–370

  109. 109.

    G.G. Robertson, J.D. Mackinlay, S.K. Card, Proc. Human Factors in Computing Systems CHI 91 Conf. (New Orleans, LA, 1991), pp. 189–194

  110. 110.

    J. Lamping, R. Rao, P. Pirolli, Proc. Human Factors in Computing Systems Conf. (1995), p. 401408

  111. 111.

    J.J. van Wijk, H. van de Wetering, Proceedings 1999 IEEE Symposium on Information Visualization (1999), p. 7378

  112. 112.

    M. Bruls, K. Huizing, J.J. Van Wijk, Proceedings of Joint Eurographics and IEEE TCVG Symposium on Visualization (IEEE Press, 2000), p. 3342

  113. 113.

    F. Frankel, R. Reid, Nature, 455, 30 (2008)

  114. 114.

    Sciencesim, http://www.sciencesim.com

  115. 115.

    S. Bryson, Comm. ACM 39, 5 (1996)

    Article  Google Scholar 

  116. 116.

    J.J. LaViola, et al., Trends in Interactive Visualization, edited by R. Liere, T. Adriaansen, E. Zudilova-Seinstra (Springer, London, 2009), pp. 1–26

  117. 117.

    D. Germans, H. Spoelder, L. Renambot, et al., IPT/EGVE (2001)

  118. 118.

    F. Araki, S. Kawahara, N. Ohno, Chap. Study of Large-Scale Data Visualization (2008), pp. 273–277

  119. 119.

    Vfive: Virtual reality visualization software for cave system, http://www.jamstec.go.jp/esc/research/Perception/vfive.en.html

  120. 120.

    Top 500 supercomputer sites, http://www.top500.org

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Helbing, D., Balietti, S. From social simulation to integrative system design. Eur. Phys. J. Spec. Top. 195, 69–100 (2011). https://doi.org/10.1140/epjst/e2011-01402-7

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Keywords

  • Virtual Reality
  • European Physical Journal Special Topic
  • Social Simulation
  • Integrative System Design
  • Decision Arena