Agent-based models

Annual Review of Political Science

Volumn 17, Issue , 2014, Pages 1-20

  De Marchi, Scott ^a   Page, Scott E ^b  

^a DUKE UNIVERSITY   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

Author keywords

Complexity; Computational; Game theory; Social science

Indexed keywords

EID: 84901016792     PISSN: 10942939     EISSN: None     Source Type: Book Series    
DOI: 10.1146/annurev-polisci-080812-191558     Document Type: Article

References (95)

1. Alchian AA. 1950. Uncertainty, evolution, and economic theory. J. Polit. Econ. 58. 3: 211-21
2. Anderson P. 1972. More is different. Science 177: 393-96
3. Andreoni J, Miller JH. 1995. Auctions with artificial adaptive agents. Games Econ. Behav. 10(1): 39-64
4. Ansolabehere S, et al. 2005. Voting weights and formateur advantages in the formation of coalition governments. Am. J. Polit. Sci. 49(3): 550-63 (Pubitemid 41638772)
5. Axelrod R. 1997. The Complexity of Cooperation. Princeton, NJ: Princeton Univ. Press
6. Axelrod R, Axtell R, Epstein J, CohenMD. 1996. Aligning simulationmodels: a case study and results. Comput. Math. Organ. Theory 1: 123-41
7. Axelrod R, Cohen MD. 2000. Harnessing Complexity: Organizational Implications of a Scientific Frontier. New York: Free Press
8. Axelrod R, MitchellW, Thomas RE, Bennett DS, Bruderer E. 1995. Coalition formation in standard-setting alliances. Manag. Sci. 41: 1493-508
9. Bak P. 1996. How Nature Works: The Science of Self-Organized Criticality. New York: Springer-Verlag
10. Bankes S. 2002. Agent-based modeling: a revolution? Proc. Natl. Acad. Sci. USA 99: 7199-200 (Pubitemid 34522711)
11. Baron DP, Ferejohn JA. 1989. Bargaining in legislatures. Am. Polit. Sci. Rev. 89: 1181-206
12. Bednar J. 2009. The Robust Federation: Principles of Design. New York: Cambridge Univ. Press
13. Bednar J, Bramson A, Jones-Rooy A, Page SE. 2010. Emergent cultural signatures and persistent diversity: a model of conformity and consistency. Ration. Soc. 22(4): 407-44
14. Bednar J, Chen Y, Liu X, Page SE. 2012. Behavioral spillovers and cognitive load in multiple games: an experimental study. Games Econ. Behav. 74(1): 12-31
15. Bednar J, Page SE. 2007. Can game(s) theory explain culture? The emergence of cultural behavior within multiple games. Ration. Soc. 19: 65-97
16. Bendor J, Diermeier D, Ting M. 2003. A behavioral model of turnout. Am. Polit. Sci. Rev. 97(2): 261-80
17. Billings D, Papp D, Schaeffer J, Szafron D. 1998. Poker as a testbed for machine intelligence research. Work. Pap., Dept. Comput. Sci., Univ. Alberta. http://poker. cs. ualberta. ca/publications. html
18. Brown GW. 1951. Iterative solutions of games by fictitious play. In Activity Analysis of Production and Allocation, ed. TC Koopmans, pp. 374-76. New York: Wiley
19. Bruch E, Mare R. 2006. Neighborhood choice and neighborhood change. Am. J. Sociol. 112: 667-709
20. Camerer. 2003. Behavioral Game Theory: Experiments in Strategic Interaction. Princeton, NJ: Princeton Univ. Press
21. Carpenter DP, Esterling KM, Lazer DMJ. 2004. Friends, brokers, and transitivity: Who informs whom in Washington politics? J. Polit. 66(1): 224-46 (Pubitemid 38284390)
22. Cederman LE. 1997. Emergent Actors in World Politics. Princeton, NJ: Princeton Univ. Press
23. Cederman LE. 2005. Computational models of social forms: advancing generative process theory. Am. J. Sociol. 110(4): 864-93
24. Conitzer V, Sandholm T. 2006. Computing the optimal strategy to commit to. Proc. Seventh ACM Conf. Electron. Commer. New York: Assoc. Comp. Mach.
25. Cutler J, de Marchi S, Gallop M, Hollenbach F, Laver M, Orlowski M. 2013. Cabinet formation and portfolio distribution in European multi-party systems. Work. Pap., Dept. Polit. Sci., Duke Univ.
26. de Marchi S. 1999. Adaptive models and electoral instability. J. Theor. Polit. 11(3): 393-419
27. de Marchi S. 2005. Computational and Mathematical Modelling in the Social Sciences. New York: Cambridge Univ. Press
28. de Marchi S, Page S. 2009. Agent-based modeling. In Oxford Handbook of Political Science Methodology, ed. JM Box-Steffensmeier, HE Brady, D Collier, pp. 71-96. New York: Cambridge Univ. Press
29. Diermeier D, Krehbiel K. 2003. Institutionalism as methodology. J. Theor. Polit. 15(2): 123-44
30. Ensley MJ, Tofias MW, de Marchi S. 2009. District complexity as an advantage in congressional elections. Am. J. Polit. Sci. 53(4): 990-1005
31. Epstein JM. 2007. Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton, NJ: Princeton Univ. Press
32. Epstein JM. 2014. Toward Neurocognitive Foundations for Generative Social Science. Princeton, NJ: Princeton Univ. Press
33. Epstein JM, Axtell R. 1996. Growing Artificial Societies: Social Science from the Bottom Up. Cambridge, MA: MIT Press
34. Epstein JM, Goedecke DM, Yu F, Morris RJ, Wagener DK, Bobashev GV. 2006. Pandemic influenza and the value of international travel restrictions. CSEDWork. Pap. 46, Brookings Inst., Washington, DC
35. Fowler J. 2006a. Connecting the Congress: a study of cosponsorship networks. Polit. Anal. 14(4): 456-87 (Pubitemid 44404541)
36. Fowler J. 2006b. Habitual voting and voter turnout. J. Polit. 68(2): 335-44
37. Fowler J. 2006c. Legislative cosponsorship networks in the U. S. House and Senate. Soc. Netw. 28(4): 454-65 (Pubitemid 44089302)
38. Fowler J, Laver M. 2008. A tournament of party decision rules. J. Conf. Resolut. 52(1): 68-92
39. Fowler J, Smirnov O. 2005. Dynamic parties and social turnout: an agent-based model. Am. J. Sociol. 110: 4
40. Gartzke E, Weisiger A. 2013. Fading friendships: alliances, affinities and the activation of international identities. Br. J. Polit. Sci. 43: 25-52
41. Gaylord R, D'Andria LJ. 1998. Simulating Society: A Mathematical Toolkit for Modeling Socioeconomic Behavior. London: Springer
42. Geanakoplos J, Axtell R, Farmer JD, Howitt P, Conlee B, et al. 2012. Getting at systemic risk via an agent-based model of the housing market. Am. Econ. Rev. 102(3): 53-58
43. Gell-Mann M. 1994. The Quark and the Jaguar: Adventures in the Simple and the Complex. New York: Freeman
44. Glaeser E, Sacerdote B, Scheinkman J. 1996. Crime and social interactions. Q. J. Econ. 111: 507-48
45. Golder M, Golder S, Siegel D. 2012. Modeling the institutional foundation of parliamentary government formation. J. Polit. 74(2): 427
46. Golman R, Page SE. 2009. Basins of attraction and equilibrium selection under different learning rules. Evol. Econ. 20: 49-72
47. Golman R, Page SE. 2010. Individual and cultural learning in stag hunt games with multiple actions. J. Econ. Behav. Organ. 73(3): 359-76
48. Hoff PD, Ward MD. 2004. Modeling dependencies in international relations networks. Polit. Anal. 12: 160-75
49. Holland J, Miller J. 1991. Artificial agents in economic theory. Am. Econ. Rev. Pap. Proc. 81: 365-70
50. Hong L, Page S. 2009. Interpreted and generated signals. J. Econ. Theory 144: 2174-96
51. Huckfeldt RR, Johnson PE, Sprague JD. 2004. Political Disagreement: The Survival of Diverse Opinions Within Communication Networks. Cambridge, UK: Cambridge Univ. Press
52. Jackson M. 2008. Social and Economic Networks. Princeton, NJ: Princeton Univ. Press
53. Jen E. 2005. Robust Design: A Repertoire of Biological, Ecological, and Engineering Case Studies. Oxford, UK: Oxford Univ. Press
54. Jervis R. 1997. System Effects: Complexity in Political and Social Life. Princeton, NJ: Princeton Univ. Press
55. Jones-Rooy A, Page SE. 2012. The Complexity of Systems Effects. Crit. Rev. 24(3): 313-42
56. Judd K. 1997. Computational economics and economic theory: complements or substitutes? J. Econ. Dyn. Control 21(6): 907-42 (Pubitemid 127166461)
57. Kauffman SA. 1993. The Origins of Order: Self-Organization and Selection in Evolution. New York: Oxford Univ. Press
58. Kim S-Y, Taber CS, Lodge M. 2010. A computational model of the citizen as motivated reasoner: modeling the dynamics of the 2000 presidential election. Polit. Behav. 32: 1-28
59. Kirman A. 1997. The economy as an interactive system. In The Economy as a Complex Evolving System II, ed. WB Arthur, S Durlauf, D Lane, pp. 491-533. Reading, MA: Addison Wesley
60. Kollman K. 2012. The potential value of computational models in social science research. In Oxford Handbook in Philosophy in the Social Sciences, ed. H Kincaid. New York: Oxford Univ. Press
61. Kollman K, Miller J, Page S. 1992. Adaptive parties in spatial elections. Am. Polit. Sci. Rev. 86: 929-37
62. Kollman K, Miller J, Page S. 1997. Political institutions and sorting in a Tiebout model. Am. Econ. Rev. 87: 977-92 (Pubitemid 127454242)
63. Kollman K, Miller J, Page S, eds. 2003. ComputationalModels of Political Economy. Cambridge, MA: MIT Press
64. Kollman K, Page S. 2005. Computational methods and models of politics. In The Handbook of Computational Economics, ed. L Tesfatsion, K Judd, pp. 1433-63. Amsterdam: Elsevier/North Holland
65. Lamberson PJ, Page SE. 2012. Tipping points. Q. J. Polit. Sci. 7(2): 175-208
66. Laver M. 2005. Policy and the dynamics of political competition. Am. Polit. Sci. Rev. 99(2): 263-81 (Pubitemid 40855831)
67. Laver M, de Marchi S, Mutlu H. 2011. Negotiation in legislatures over government formation. Public Choice 147: 285-304
68. Laver M, Sergenti E. 2011. Party Competition: An Agent-Based Model. Princeton, NJ: Princeton Univ. Press
69. Lazer D. 2001. The co-evolution of individual and network. J. Math. Sociol. 25: 69-108 (Pubitemid 33397471)
70. LeBaron B. 2001. Stochastic volatility as a simple generator of apparent financial power laws and long memory. Q. Financ. 1: 621-31
71. Leombruni R, Richiardi M. 2005. Why are economists sceptical about agent-based simulations? Phys. A 355(1): 103-9 (Pubitemid 40915169)
72. Lodge M, Sung-Youn K, Charles T. 2004. A computational model of political cognition - the dynamics of candidate evaluation in the 2000 presidential election. Presented at Annu. Meet. Midwest Polit. Sci. Assoc., Chicago
73. Lustick I, Miodownik D. 2000. Deliberative democracy and public discourse: the agent-based argument repertoire model. Complexity 5(4): 13-30
74. Lustick I, Miodownik D, Eidelson RJ. 2004. Secessionism in multicultural states: Does sharing power prevent or encourage it? Am. Polit. Sci. Rev. 98(2): 209-29 (Pubitemid 38860572)
75. Miller J. 1998. Active nonlinear tests (ANTs) of complex simulations models. Manag. Sci. 44: 820-30 (Pubitemid 128572652)
76. Miller J, Page S. 2007. Complex Adaptive Systems: Computational Models of Social Life. Princeton, NJ: Princeton Univ. Press
77. Mitchell M. 2009. Complexity: A Guided Tour. Oxford, UK: Oxford Univ. Press
78. Newman MJ. 2003. On the logic and structure of complex networks. SIAM Rev. 45: 167-256
79. Nowak M, Bonhoeffer S, May R. 1994. Spatial games and the maintenance of cooperation. Proc. Natl. Acad. Sci. USA 91: 4877-81 (Pubitemid 24177753)
80. Nowak M, May RM. 1992. Evolutionary games and spatial chaos. Nature 359: 826-29 (Pubitemid 23398292)
81. Ostrom E. 1990. Governing the Commons: The Evolution of Institutions for Collective Action. Cambridge, UK: Cambridge Univ. Press
82. Page SE. 1997. On incentives and updating in agent based models. Comput. Econ. 10: 67-87 (Pubitemid 127505754)
83. Page SE. 2006. Essay: path dependence. Q. J. Polit. Sci. 1(1): 87-115
84. Page SE. 2007. The Difference: How the Power of Diversity Creates Better Groups, Teams, Schools, and Societies. Princeton, NJ: Princeton Univ. Press
85. Page SE. 2008. Uncertainty, difficulty, and complexity. J. Theor. Polit. 20: 115-49
86. Page SE. 2011. Diversity and Complexity. Princeton, NJ: Princeton Univ. Press
87. Palmer R, Arthur W, Holland J, Lebaron B, Tayler P. 1994. Artificial economic life: a simple model of a stock market. Phys. D 75: 264-74
88. Richards D. 2000. Nonlinear dynamics in games: convergence and stability in international environmental agreements. In Political Complexity: Nonlinear Models of Politics, ed. D Richards, pp. 173-206. Ann Arbor: Univ. Michigan Press
89. Schelling T. 1978. Micromotives and Macrobehavior. New York: Norton
90. Smirnov O, Fowler JH. 2007. Policy-motivated parties in dynamic political competition. J. Theor. Polit. 19(1): 9-31
91. Tesfatsion L. 1997. How economists can get alife. In The Economy as a Complex Evolving System II, ed. WArthur, S Durlauf, D Lane, pp. 533-65. Reading, MA: Addison Wesley
92. Vriend N. 2000. An illustration of the essential difference between individual and social learning, and its consequences for computational analyses. J. Econ. Dyn. Control 24: 1-19
93. Weidmann N, Salehyan I. 2013. Violence and ethnic segregation: a computational model applied to Baghdad. Int. Stud. Q. 57: 52-64
94. Wichowsky A. 2012. District complexity and the personal vote. Legis. Stud. Q. 37(4): 437-63
95. Zinkevich M, Bowling M, Johanson M, Piccione C. 2007. Regret minimization in games with incomplete information. Presented at Neural Inf. Process. Syst., Dec. 3-6, British Columbia, Can. http://books. nips.cc/nips20.html