Agent-based modeling

Understanding Complex Systems

Volumn , Issue , 2012, Pages 25-70

  Helbing, Dirk ^a  

^a ETH ZURICH   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84861829371     PISSN: 18600832     EISSN: 18600840     Source Type: Book Series    
DOI: 10.1007/978-3-642-24004-1_2     Document Type: Article

References (189)

1. D. Helbing, S. Balietti, From social data mining to forecasting socio-economic crisis. visioneer white paper (2010) http://www.visioneer.ethz. ch.
2. N. Gilbert, K.G. Troitzsch, Simulation for the Social Scientist. (Open University Press, England, 2005)
3. J.M. Epstein, R. Axtell, Growing artificial societies. (Cambridge, MA, 1996)
4. J.M. Epstein, Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton Studies in Complexity. (Princeton University Press, Princeton, 2007)
5. N.R. Jennings, On agent-based software engineering. Artif. Intell. 117(2), 277-296 (2000)
6. A.M. Uhrmacher, D.Weyns, Multi-Agent Systems: Simulation and Applications. (CRC Press, Inc., Boca Raton, FL, USA, 2009)
7. N. Gilbert, S. Bankes, Platforms and methods for agent-based modeling. Proc. Natl. Acad. Sci. USA 99(Suppl 3), 7197 (2002)
8. M.W. Macy, R. Willer, From factors to actors: computational sociology and agent-based modeling. Annu. Rev. Sociol. 28(1), 143-166 (2002)
9. J.P. Davis, K.M. Eisenhardt, C.B. Bingham, Developing theory through simulation methods. Acad. Manag. Rev. 32(2), 480 (2007)
10. R.A. Bentley, P. Ormerod, Agents, intelligence, and social atoms, in Creating Consilience: Integrating the Sciences and the Humanities, ed. by M. Collard, E. Slingerland (Oxford University Press, 2011)
11. D. Helbing, Pluralistic modeling of complex systems (2010) CCSS-10-009
12. J.M. Epstein,Why model? J. Artif. Soc. Soc. Simulat. 11(4), 12 (2008). http://jasss.soc.surrey. ac.uk/11/4/12.html
13. D. Helbing, S. Balietti, Fundamental and real-world challenges in economics. Sci. Cult. 76, 399-417 (2010). Special Issue: 15 year of econophysics research
14. D. Helbing, A. Szolnoki, M. Perc, G. Szabó, Evolutionary establishment of moral and double moral standards through spatial interactions. PLoS Comput. Biol. 6(4), e1000758, 04 (2010)
15. R. May, A. McLean, Theoretical Ecology: Principles and Applications, 3rd edn. (Oxford University Press, USA, 2007)
16. I. Foster, A two-way street to science's future. Nature 440, 419 (2006)
17. C.S. Taber, R.J. Timpone, Computational Modelign. (Sage, London, 1996)
18. F. Schweitzer, Brownian Agents and Active Particles. On the Emergence of Complex Behavior in the Natural and Social Sciences. (Springer, Berlin, 2003)
19. D. Helbing, J. Keltsch, P. Molnar, Modelling the evolution of human trail systems. Nature 388(6637), 47-50 (1997)
20. J.M. Epstein, Modelling to contain pandemics. Nature 460(7256), 687 (2009)
21. J. Parker, J. Epstein, A global-scale distributed agent-based model of disease transmission, ACM Transactions on Modelling and Computer Simulation (TOMACS) 22(1), (2011)
22. M. Treiber, A. Hennecke, D. Helbing, Congested traffic states in empirical observations and microscopic simulations. Phys. Rev. E 62, 1805 (2000)
23. D. Helbing, Derivation of non-local macroscopic traffic equations and consistent traffic pressures from microscopic car-following models. Eur. Phys. J. B 69(4), 539-548 (2009)
24. R.K. Sawyer, Artificial Societies. Socio. Meth. Res. 31(3), 325 (2003)
25. H.J. Aaron, Distinguished lecture on economics in government: Public policy, values, and consciousness. J. Econ. Perspect. 8(2), 3-21 (1994). http://ideas.repec.org/a/aea/jecper/ v8y1994i2p3-21.html
26. A.P. Kirman, Whom or what does the representative individual represent? J. Econ. Perspect. 6(2), 117-36 (1992). http://ideas.repec.org/a/aea/jecper/ v6y1992i2p117-36.html
27. D. Helbing, M. Treiber, A. Kesting, M. Schönhof, Theoretical vs. empirical classification and prediction of congested traffic states. Eur. Phys. J. B 69(4), 583-598 (2009)
28. D. Helbing, Verkehrsdynamik. (Springer, Berlin, 1997)
29. D. Helbing, Managing Complexity: Insights, Concepts, Applications, 1st edn. (Springer, Berlin, 2007)
30. D. Helbing, Systemic risks in society and economics (2009). Sante Fe Institute, working paper 09-12-044.
31. R. Kuehne, Freeway control using a dynamic traffic flow model and vehicle reidentification techniques. Transport. Res. Record 1320, 251-259 (1991)
32. B.S. Kerner, P. Konhäuser, Cluster effect in initially homogeneous traffic flow. Phys. Rev. E 48(4), 2335+ (1993)
33. R.E. Chandler, R. Herman, E.W. Montroll, Traffic dynamics: studies in car following. Oper. Res., 165-184 (1958)
34. R. Herman, E.W. Montroll, R.B. Potts, R.W. Rothery, Traffic dynamics: analysis of stability in car following. Oper. Res. 7(1), 86-106 (1959)
35. D. Helbing, M. Treiber, Critical discussion of "synchronized flow". Cooper. Transport. Dyn. 1, 2.1-2.24 (2002)
36. D. Helbing, T. Seidel, S. Laemmer, K. Peters, Econophysics and Sociophysics-Trends and Perspectives, chapter Self-organization principles in supply networks and production systems (Wiley, Weinheim, 2006), pp. 535-558
37. D. Helbing, A. Mazloumian, Operation regimes and slower-is-faster effect in the control of traffic intersections. Eur. Phys. J. B 70(2), 257-274 (2009)
38. Dirk Helbing, Illés J. Farkas, and Tamás Vicsek, Freezing by Heating in a Driven Mesoscopic System. Phys. Rev. Lett. 84(6), 1240-1243 (2000)
39. D. Helbing, W. Yu, The outbreak of cooperation among success-driven individuals under noisy conditions. Proc. Natl. Acad. Sci. 106(10), 3680-3685 (2009)
40. S. Laemmer, D. Helbing, Self-control of traffic lights and vehicle flows in urban road networks. JSTAT (2008). P04019
41. Michael Mäs, Andreas Flache, and Dirk Helbing, Individualization as Driving Force of Clustering Phenomena in Humans. PLoS Comput. Biol. 6(10), e1000959+ (2010)
42. J. Lorenz, H. Rauhut, F. Schweitzer, D. Helbing, How social influence undermines the wisdom of crowds. Proc. Natl. Acad. Sci. USA (PNAS) 108(22), 9020-9025 (2011)
43. D. Helbing, W. Yu, K.-D. Opp, H. Rauhut, The emergence of homogeneous norms in heterogeneous populations. Santa Fe Working Paper 11-01-001 (2011), see http://www. santafe.edu/media/workingpapers/11-01-001.pdf, last accessed on March 6, 2012
44. C. Nardini, B. Kozma, A. Barrat, Who's talking first? consensus or lack thereof in coevolving opinion formation models. Phys. Rev. Lett. 100(15), 158701 (2008)
45. J.S. Sichman, Depint: Dependence-based coalition formation in an open multi-agent scenario. JASSS J. Artif. Soc. Soc. Simulat. 1(2) (1998)
46. M.E. Gaston, M. des Jardins, Agent-organized networks for dynamic team formation. In Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, AAMAS '05, pages 230-237, New York, NY, USA, 2005. ACM
47. E. Bonabeau, M. Dorigo, G. Theraulaz, Inspiration for optimization from social insect behaviour. Nature 406(6791), 39-42 (2000)
48. G. Szabo, G. Fath, Evolutionary games on graphs. Phys. Rep. 446(4-6), 97-216 (2007)
49. P.J. Carrington, J. Scott, S. Wasserman, Models and Methods in Social Network Analysis. (Cambridge University Press, Cambridge, 2005)
50. P. Holme, G. Ghoshal, Dynamics of networking agents competing for high centrality and low degree. Phys. Rev. Lett. 96(9), 098701 (2006)
51. M. Sierhuis, J.M. Bradshaw, A. Acquisti, R. van Hoof, R. Jeffers, A. Uszok, Human-Agent Teamwork and Adjustable Autonomy in Practice. In Proceedings of the seventh international symposium on artificial intelligence, robotics and automation in space (I-SAIRAS), 2003
52. Robert Axelrod, The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, 1st printing edn. (Princeton University Press, Princeton, 1997)
53. S. Bowles, H. Gintis, The evolution of strong reciprocity: cooperation in heterogeneous populations. Theor. Popul. Biol. 65(1), 17-28 (2004)
54. D. Helbing, A. Johansson, Cooperation, norms, and conflict: A unified approach (2009) SFI Working Paper
55. Heiko Rauhut and Marcel Junker, Punishment deters crime because humans are bounded in their strategic decision-making. J. Artif. Soc. Soc. Simulat. 12(3), 1 (2009)
56. L-E. Cederman, Modeling the size of wars: From billiard balls to sandpiles. Am. Polit. Sci. Rev. 97, 135-150 (2003)
57. L-E. Cederman, Emergent Actors in World Politics: How States and Nations Develop and Dissolve. (Princeton University Press, Princeton, NJ, 1997)
58. C. Hommes, Chapter 23 Heterogeneous Agent Models in Economics and Finance, in Handbook of Computational Economics, vol. 2 (Elsevier, 2006), pp. 1109-1186
59. B. LeBaron, Building the santa fe artificial stock market. Physica A, 2002. Working Paper, Brandeis University.
60. M. Raberto, S. Cincotti, S.M. Focardi, M. Marchesi, Agent-based simulation of a financial market. Phys. Stat. Mech. Appl. 299(1-2), 319-327 (2001)
61. J. Zhang, Growing Silicon Valley on a landscape: an agent-based approach to high-tech industrial clusters. Entrepreneurships, the New Economy and Public Policy, pp. 71-90 (2005)
62. Robert Axtell, The emergence of firms in a population of agents. Working Papers 99-03-019, Santa Fe Institute, March 1999
63. T. Kaihara, Multi-agent based supply chain modelling with dynamic environment. Int. J. Prod. Econ. 85(2), 263-269 (2003)
64. C. Preist, Commodity trading using an agent-based iterated double auction, in Proceedings of the third annual conference on Autonomous Agents (ACM 1999), pp. 131-138.
65. Lebaron, Blake, Tesfatsion, Leigh, Modeling macroeconomies as open-ended dynamic systems of interacting agents. Am. Econ. Rev. 98(2), 246-250 (2008)
66. Leigh Tesfatsion, Agent-based computational economics: growing economies from the bottom up. Artif. Life 8(1), 55-82 (2002)
67. J.R. Harrison, Z. Lin, G.R. Carroll, K.M. Carley, Simulation modeling in organizational and management research. Acad. Manag. Rev. 32(4), 1229 (2007)
68. B.S. Onggo, Parallel discrete-event simulation of population dynamics. In Proceedings of Winter Simulation Conference 2008 (Miami, FL, USA), pp. 1047-1054
69. Y. Mansury, M. Kimura, J. Lobo, T.S. Deisboeck, Emerging patterns in tumor systems: simulating the dynamics of multicellular clusters with an agent-based spatial agglomeration model. J. Theor. Biol. 219(3), 343-370 (2002)
70. D. Osullivan, J.M Macgill, C. Yu, Agent-based residential segregation: a hierarchically structured spatial model. Agent 2003 Challenges in Social Simulation (2003)
71. M. Batty, Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals. (The MIT Press, Cambridge, 2007)
72. D. Helbing, K. Nagel, The physics of traffic and regional development. Contemp. Phys. 45(5), 405-426 (2004)
73. V. Killer, K.W. Axhausen, D. Guth, C. Holz-Rau, Understanding regional effects of travel times in switzerland and germany 1970-2005. Jonkoping, Sweden, August 2010. 50th European Regional Science Association (ERSA)
74. C.R. Binder, C. Hofer, A. Wiek, R.W. Scholz, Transition towards improved regional wood flows by integrating material flux analysis and agent analysis: the case of appenzell ausserrhoden, switzerland. Ecol. Econ. 49(1), 1-17 (2004)
75. H. Dia, An agent-based approach to modelling driver route choice behaviour under the influence of real-time information. Transport. Res. C Emerg. Tech. 10(5-6), 331-349 (2002)
76. C.M. Henein, T.White, Agent-based modelling of forces in crowds, in Multi-agent and Multiagent-Based Simulation (Springer, Berlin, 2005), pp. 173-184
77. M. Batty, Agent-based pedestrian modelling, in Advanced spatial analysis: the CASA book of GIS, page 81 (2003)
78. D. Delli Gatti, Emergent macroeconomics : an agent-based approach to business fluctuations. (Springer, Berlin, 2008)
79. M. Aoki, H. Yoshikawa, Reconstructing Macroeconomics: A Perspective from Statistical Physics and Combinatorial Stochastic Processes (Japan-US Center UFJ Bank Monographs on International FinancialMarkets), 1st edn. (Cambridge University Press, Cambridge, 2006)
80. R. Conte, R. Hegselmann, P. Terna, Simulating Social Phenomena. (Springer, Berlin, 1997)
81. R. Sun (ed.), Cognition and Multi-Agent Interaction: From Cognitive Modeling to Social Simulation, 1st edn. (Cambridge University Press, Cambridge, 2008)
82. N. Gilbert, Agent-Based Models. (Sage Publications, Inc, 2007)
83. V. Grimm, E. Revilla, U. Berger, F. Jeltsch, W.M. Mooij, S.F. Railsback, H.H. Thulke, J. Weiner, T. Wiegand, D.L. DeAngelis, Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science 310(5750), 987 (2005)
84. R. Axelrod, Advancing the art of simulation in the social sciences, in Handbook of Research on Nature Inspired Computing for Economy and Management, ed. by Jean-Philippe Rennard (Hersey, PA, 2005)
85. K. Nagel, Parallel implementation of the transims micro-simulation. Parallel Comput. 27(12), 1611-1639 (2001)
86. M. Rickert, K. Nagel, Dynamic traffic assignment on parallel computers in transims. Future Generat. Comput. Syst. 17(5), 637-648 (2001)
87. K. Nagel, R.J. Beckman, C.L. Barrett, Transims for urban planning. Los Alamos Unclassified Report (LA-UR) 98-4389, Los Alamos National Laboratory (1999)
88. K. Nagel, C.L. Barrett, Using microsimulation feedback for trip adaptation for realistic traffic in Dallas. Santa Fe Working Paper 97-03-028 (1997), see http://www.santafe.edu/media/workingpapers/97-03-028.pdf, last accessed on March 6, 2012
89. P.M. Simon, J. Esser, and Nagel K. Simple queueing model applied to the city of portland. Int. J. Mod. Phys. C 10(5), 941-960 (1999)
90. B. Raney, N. Cetin, A. Vollmy, M. Vrtic, Axhausen. K., K. Nagel, An agent-based microsimulation model of swiss travel: First results. Network Spatial. Econ. 3, 23-41 (2003)
91. M. Balmer, K.W. Axhausen, K. Nagel, An agent based demand modeling framework for large scale micro-simulations (2005) Working paper, 329, Institute for Transport Planning and Systems (IVT), ETH Zurich, Switzerland.
92. D. Charypar, K. Nagel, Generating complete all-day activity plans with genetic algorithms. Transportation 32(4), 369-397 (2005)
93. K.W. Axhausen, T. Garling, Activity-based approaches to travel analysis: conceptual frameworks, models, and research problems. Transport Rev. 12(4), 323-341 (1992)
94. G. Laemmel, D. Grether, K. Nagel, The representation and implementation of time-dependent inundation in large-scale microscopic evacuation simulations. Transport. Res. C Emerg. Tech. 18(1), 84-98 (2010)
95. H. Taubenboeck, N. Goseberg, N. Setiadi, G. Laemmel, F. Moder, M. Oczipka, H. Klupfel, Roland Wahl, T. Schlurmann, G. Strunz, J. Birkmann, K. Nagel, F. Siegert, F. Lehmann, S. Dech, A. Gress, R. Klein, "last- mile" preparation for a potential disaster-interdisciplinary approach towards tsunami early warning and an evacuation information system for the coastal city of padang, indonesia. Nat. Hazards Earth Syst. Sci. 9(4), 1509-1528 (2009). http://www. nat-hazards-earth-syst-sci.net/9/1509/2009
96. J. Min, J.E. Beyler, Brown T.H., Y. Jun Son, A.T. Jones, Toward modeling and simulation of critical national infrastructure interdependencies. IIE Trans., 57-71 (2007) special issue on Industrial Engineering and Operations Research in Homeland Security.
97. C. Barrett, S. Eubank, M. Marathe, Modeling and simulation of large biological, information and socio-technical systems: An interaction based approach, in Interactive Computation, ed. by D. Goldin, S.A. Smolka, P.Wegner (Springer, Berlin, 2006), pp. 353-392. 10.1007/3-540-34874-3 14
98. National Infrastructure Simulation and Analysis Center (NISAC), see http://www.lanl.gov/ programs/nisac/, last accessed on March 6, 2012
99. W. Kermack, A. Mckendrick, Contributions to the mathematical theory of epidemics-i. Bull. Math. Biol. 53(1), 33-55 (1991)
100. W. Kermack, A. Mckendrick, Contributions to the mathematical theory of epidemics-ii. the problem of endemicity. Bull. Math. Biol. 53(1), 57-87 (1991)
101. W. Kermack, A. McKendrick, Contributions to the mathematical theory of epidemics-iii. further studies of the problem of endemicity. Bull. Math. Biol. 53(1), 89-118 (1991)
102. V. Colizza, A. Barrat, M. Bartholemy, A. Vespignani, The role of the airline transportation network in the prediction and predictability of global epidemics. Proc. Natl. Acad. Sci. USA 103(7), 2015-2020 (2006)
103. L. Hufnagel, D. Brockmann, T. Geisel, Forecast and control of epidemics in a globalized world. Proc. Natl. Acad. Sci. USA 101(42), 15124-15129 (2004)
104. S. Eubank, H. Guclu, Anil K.V.S., M.V. Marathe, A. Srinivasan, Z. Toroczkai, N. Wang, Modelling disease outbreaks in realistic urban social networks. Nature 429(6988), 180-184 (2004)
105. Artificial stock market, see http://sourceforge.net/projects/artstkmkt/, last accessed on March 6, 2012
106. U-mart. http://www.u-mart.org/, last accessed on March 6, 2012
107. Eurace. http://www.eurace.org/, last accessed on March 6, 2012
108. A. Cangelosi, D. Parisi, Simulating the evolution of language. (Springer, Berline, 2002)
109. R. Dunbar, Grooming, gossip, and the evolution of language. (Harvard University Press, Cambridge, 1998)
110. M.A. Nowak, D.C. Krakauer, The evolution of language. Proc. Natl. Acad. Sci. USA 96(14), 8028 (1999)
111. D. Helbing, S. Balietti, How to create an innovation accelerator. Eur. Phys. J. Special Topics 195, 101-136 (2011)
112. M. Eigen, P. Schuster, The Hypercycle. Naturwissenschaften 65(1), 7-41 (1978)
113. R.K. Merton, The Matthew effect in science. The reward and communication systems of science are considered. Science (New York, N.Y.) 159(810), 56-63 (1968)
114. M. Mcpherson, L. Smith-Lovin, J.M. Cook, Birds of a Feather: Homophily in Social Networks. Annu. Rev. Sociol. 27, 415-444 (2001)
115. N.A. Christakis, J.H. Fowler, The spread of obesity in a large social network over 32 years. New Engl. J. Med. 357(4), 370-379 (2007)
116. N.A. Christakis, J.H. Fowler, The Collective Dynamics of Smoking in a Large Social Network. New Engl. J. Med. 358(21), 2249-2258 (2008)
117. K.P. Smith, N.A. Christakis, Social Networks and Health. Annu. Rev. Sociol. 34(1), 405-429 (2008)
118. T. Chadefaux, D. Helbing, How wealth accumulation can promote cooperation. PLoS One 5(10), e13471, 10 (2010)
119. D. Helbing, W. Yu, H. Rauhut, Self-organization and emergence in social systems: Modeling the coevolution of social environments and cooperative behavior. J.Math. Sociol. 35, 177-208 (2011)
120. A.P. Fiske, Structures of Social Life: The Four Elementary Forms of Human Relations: Communal Sharing, Authority Ranking, Equality Matching, Market Pricing. (Free Press, 1991)
121. Mark Granovetter, The strength of weak ties: a network theory revisited. Sociol. Theor. 1, 201-233 (1982)
122. G. Gigerenzer, P.M. Todd, ABC Research Group, Simple Heuristics That Make Us Smart (Oxford University Press, New York, 2000)
123. W.H. Greene, Econometric Analysis. (Prentice Hall, Upper Saddle River, NJ., 2008). Particularly Chap. 7.4: Model selection criteria
124. F. Diebold, Elements of forecasting, 3rd edn. (Thomson/South-Western, Mason, Ohio, 2003)
125. Swarm, http://www.swarm.org/, last accessed on March 6, 2012
126. Repast, recursive porous agent simulation toolkit. http://repast. sourceforge.net/, last accessed on March 6, 2012
127. Netlogo, http://ccl.northwestern.edu/netlogo/, last accessed on March 6, 2012
128. Sesam, shell for simulated agent systems. http://www.simsesam.de/, last accessed on March 6, 2012
129. Massive software. http://www.massivesoftware.com/, last accessed on March 6, 2012
130. Wikipedia: Comparison of agent-based modeling software. http://en.wikipedia.org/wiki/ Comparison of agent-based modeling software, last accessed on March 6, 2012
131. S.F. Railsback, S.L. Lytinen, S.K. Jackson, Agent-based simulation platforms: review and development recommendations. Simulation 82(9), 609-623 (2006)
132. CVS Concurrent Version System. http://www.nongnu.org/cvs/, last accessed on March 6, 2012
133. Subversion, http://subversion.apache.org/, last accessed on March 6, 2012
134. Bazaar, http://bazaar.canonical.com/en/, last accessed on March 6, 2012
135. Git-fast version control system. http://git-scm.com
136. D. Helbing, A. Johansson, Pedestrian, crowd and evacuation dynamics, in Encyclopedia of Complexity and Systems Science (Springer, Berlin, 2010), pp. 6476-6495
137. D. Helbing, A. Johansson, L. Buzna, Modelisation Du Traffic-Actes du groupe de travail, chapter New design solutions for pedestrian facilities based on recent empirical results and computer simulations, pp. 67-88. (2003) Actes No. 104
138. E. Brockfeld, R.D. Kuehne, P. Wagner, Toward benchmarking of microscopic traffic flow models. Transport. Res. Record 1852, 124-129 (2004)
139. E. Brockfeld, R.D. Kuehne, P. Wagner, Calibration and validation of microscopic traffic flow models. Transport. Res. Record 1876, 62-70 (2004)
140. D. Helbing, M. Schreckenberg, Cellular automata simulating experimental properties of traffic flows. Phys. Rev. E 59, R2505-R2508 (2010)
141. A.G. Hoekstra, J. Kroc, P.M.A. Sloot (eds.), chapter Game theoretical interactions of moving agents, in Simulating Complex Systems by Cellular Automata (Springer, Berlin, 2010), pp.219-239
142. D. Helbing, W. Yu, The future of social experimenting. PNAS 107(12), 5265-5266 (2010)
143. D. Helbing, T. Platkowski, Self-organization in space and induced by fluctuations. Int. J. Chaos Theor. Appl. 5(4), (2000)
144. R.J. LeVeque, Numerical Methods for Conservation Laws. (Birkhauser, Basel, 1992)
145. K. De Jong, Evolutionary computation: a unified approach, in GECCO '08: Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation (ACM, New York, NY, USA, 2008), pp. 2245-2258
146. P. Ciaccia, M. Patella, P. Zezula, M-tree: An Efficient Access Method for Similarity Search in Metric Spaces. VLDB J. 426-435 (1997)
147. L.A. Wolsey, An analysis of the greedy algorithm for the submodular set covering problem. Combinatorica 2(4), 385-393 (1982)
148. D. Freedman, R. Pisani, R. Purves, Statistics. (W. W. Norton & Company, New York, 1997)
149. E.C. Zeeman, Catastrophe Theory: Selected Papers, 1972-1977 (Addison-Wesley, 1980)
150. T.S. Kuhn, The Structure of Scientific Revolutions. (University Of Chicago Press, Chicago, 1962)
151. D. Helbing, A. Johansson, Evolutionary dynamics of populations with conflicting interactions: Classification and analytical treatment considering asymmetry and power. Phys. Rev. E 81, 016112+ (2010)
152. D. Helbing, A. Johansson, Cooperation, Norms, and Revolutions: A Unified Game-Theoretical Approach. PLoS ONE 5, e12530 (2010)
153. Benedikt Herrmann, Christian Thöni, and Simon Gächter. Antisocial Punishment Across Societies. Science 319(5868), 1362-1367 (2008)
154. D. Helbing, Quantitative Sociodynamics: Stochastic Methods and Models of Social Interaction Processes. (Springer, Berlin, 2010)
155. V. Nemytsky, V. Stepanov, Qualitative theory of differential equations. (Princeton University Press, Princeton NJ, 1960)
156. R. Albert, H. Jeong, A.-L. Barabasi, Error and attack tolerance of complex networks. Nature 406, 378-382 (2000)
157. M. Olson, The Logic of Collective Action : Public Goods and the Theory of Groups. Harvard economic studies, v. 124. (Harvard University Press, Cambridge, MA, 1971)
158. M. Moussaid, D. Helbing, S. Garnier, A. Johansson, M. Combe, G. Theraulaz, Experimental study of the behavioural mechanisms underlying self-organization in human crowds. Proc. Biol. Sci. B: Biol. Sci. 276(1668), 2755-2762 (2009)
159. M. Treiber, A. Kesting, D. Helbing, Three-phase traffic theory and two-phase models with a fundamental diagram in the light of empirical stylized facts. Transport. Res. B: Methodological, 44(8-9), 983-1000 (2010)
160. A.-L. Barabási, R. Albert, Emergence of Scaling in Random Networks. Science 286(5439), 509-512 (1999)
161. John P. Ioannidis, WhyMost Published Research Findings Are False. PLoS Med. 2(8), e124+ (2005)
162. I. Fisher, The Theory of Interest. (Augustus M. Kelley Publishers, NJ, 1930)
163. B.B. Mandelbrot, The variation of certain speculative prices. J. Bus. 36, 394-419 (1963)
164. R.N.Mantegna, E.H. Stanley, An Introduction to Econophysics: Correlations and Complexity in Finance. (Cambridge University Press, New York, 1999)
165. V. Pareto, Translation of Manuale di economia politica ("Manual of political economy"). (A.M. Kelley, New york, 1971)
166. George Zipf, The economy of geography (Addison-Wesley Publishing Co. Inc, Cambridge, 1949), pp.347-415
167. Ravenstein E. The birthplaces of the people and the laws of migration. The Geographical Magazine III, pp. 173-177, 201-206, 229-233 (1876)
168. G.K. Zipf, The p1 p2/d hypothesis: on the intercity movement of persons. Am. Soc. Rev. 11, 677-686 (1946)
169. J. Tinbergen, Shaping the world economy: suggestions for an international economic policy. (Twentieth Century Fund, New York, 1962)
170. C.A.E. Goodhart, Monetary relationships: a view from Threadneedle Street. Papers monetary Econ. 1 (1975)
171. J. Danielsson, The emperor has no clothes: Limits to risk modelling. J. Bank. Finance 26(7), 1273-1296 (2002)
172. D. Helbing, M. Treiber, N.J. Saam, Analytical investigation of innovation dynamics considering stochasticity in the evaluation of fitness. Phys. Rev. E 71, 067101 (2005)
173. D. Helbing, H. Ammoser, C. Kuehnert, chapter Disasters as extreme events and the importance of network interactions for disaster response management, in Extreme Events in Nature and Society (Springer, Berlin, 2005), pp. 319-348
174. Verfahren zur Koordination von vernetzten Abfertigungsprozessen oder zur Steuerung des Transports von mobilen Einheiten innerhalb eines Netzwerkes, (2010), see http://www.patentde. com/20100805/DE102005023742B4.html, last accessed on March 6, 2012
175. D. Helbing, A. Deutsch, S Diez, K Peters, Y Kalaidzidis, K. Padberg-Gehle, S. Laemmer, A. Johansson, G. Breier, F. Schulze, M. Zerial, Biologistics and the struggle for efficiency: concepts and perpesctives. Adv. Complex Syst. 12(06), 533+ (2009)
176. L. Hurwicz, Optimality and informational efficiency in resource allocation processes, in Mathematical Methods in the Social Sciences, ed. by K.J. Arrow, S. Karlin, P. Suppes (Stanford University Press, Stanford, CA, 1960), pp. 27-46
177. A. Kesting, M. Treiber, M. Schonhof, D. Helbing, Adaptive cruise control design for active congestion avoidance. Transport. Res. C Emerg. Tech. 16(6), 668-683 (2008)
178. D. Helbing, chapter Dynamic decision behavior and optimal guidance through information services: Models and experiments, in Human Behaviour and Traffic Networks (Springer, Berlin, 2004), pp. 47-95
179. D. Helbing, M. Christen, Physik der Finanzmärkte (Wirtschaftswoche, December 22, 2010)
180. N. Wiener, Cybernetics, Second Edition: or the Control and Communication in the Animal and the Machine. (The MIT Press, Cambridge, MA, 1965)
181. B. Fabien, Analytical System Dynamics: Modeling and Simulation. (Springer, Berlin, 2008)
182. S. Skogestad, I. Postlethwaite, Multivariable Feedback Control: Analysis and Design, 2nd edn. (Wiley-Interscience, New York, 2005)
183. A.L. Fradkov, I.V. Miroshnik, V.O. Nikiforov, Nonlinear and Adaptive Control of Complex Systems. (Springer, Berlin, 1999)
184. A. Johansson, D. Helbing, P. Shukla, Specification of the social force pedestrian model by evolutionary adjustment to video tracking data. Adv. Complex Syst. 10, 271-288 (2007)
185. Google flu trends. http://www.google.org/flutrends/, last accessed on March 6, 2012
186. J. Vernon Henderson, A. Storeygard, D.N. Weil, Measuring economic growth from outer space. Technical Report 15199, National Bureau of Economic Research, July (2009) http:// www.nber.org/papers/w15199.
187. N.A. Christakis, J.H. Fowler, Social network sensors for early detection of contagious outbreaks. PloS one 5(9), e12948+, September (2010)
188. L. Buzna, K. Peters, H. Ammoser, C. Kuehnert, D. Helbing, Efficient response to cascading disaster spreading. Phys. Rev. E 75, 056107 (2006)
189. D. Helbing, S. Balietti, From social simulation to intgrative system design. visioneer white paper, 2010. http://www.visioneer.ethz.ch.