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ABM Applications to the Social Sciences

ABM Applications to the Social Sciences. Lars-Erik Cederman Department of Government, Harvard EITM Workshop, July 18, 2002. Outline: Applications. Three types of agent-based models Example: Barabasi’s Preferential Attachment Model Applications to political science

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ABM Applications to the Social Sciences

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  1. ABM Applications to the Social Sciences Lars-Erik Cederman Department of Government, Harvard EITM Workshop, July 18, 2002

  2. Outline: Applications • Three types of agent-based models • Example: Barabasi’s Preferential Attachment Model • Applications to political science • Example: GeoSim and the democratic peace • Validation

  3. actor actor actor actor actor actor actor actor actor actor actor actor actor actor actor actor actor actor Three types of emergent effects Emergent behavioral patterns D C actor actor actor Emergent boundaries and networks actor actor Emergent cultural configurations

  4. Barabasi’s Preferential Attachment Model • A. L. Barabasi et al. 1999. “Mean-field theory for scale-free random networks.” Physica A 272: 173-187.

  5. Applications to political science • Cooperation theory: Axelrod etc. • Voting and party politics: Kollman, Miller, & Page 1992 • Ethnic conflict: Bhavnani & Backer 2000; Epstein et al 2001; Lustick 2000; Cederman 2001 • Geopolitical models: Bremer & Mihalka 1977; Cusack and Stoll 1990; Cederman 1997

  6. Modeling the democratic peace with agent-based modeling • Assume the democratic peace hypothesisto hold at the micro-level • How can the democratic peace spreadto the entire state system? • Reference: “Modeling the Democratic Peace as a Kantian Selection Process” Journal of Conflict Resolution (August 2001).

  7. Outline 1. Modeling geopolitics 2. Adding tags 3. Adding alliances 4. Adding collective security 5. Replications 6. Conclusions

  8. Modeling geopolitics: GeoSim • Hobbesian geopolitical environment • Cederman 1997 Emergent Actors=> RePast • 15 x 15 grid • local combat and conquest • two types of actors: • non-democratic states: power-seekers • democratic states: conditional cooperators

  9. A dynamic network on a grid

  10. “Tagged” decision rule for democratic state i forall external fronts j do if i or j foughtor j attacked an ally of ithen attack j elsecooperate with j {Grim Trigger} ifthere is no action on any frontthen randomly select a non-democratic neighbor state j* with probabilityp(i,j*) factoring in alliancesdo launch unprovoked attack against j*

  11. Threshold functions Probability Decision to attack p(i,j*) Combat victory Force ratio

  12. Structural change: conquest • Conquest follows victorious battles • Each attacker randomly selects a “battle path” consisting of an attacking province and a target • The outcome depends on the target’s nature: • if it is an atom, the whole target is absorbed • if it is a capital, the target state collapses • if it is a province, the target is absorbed

  13. Guaranteeing territorial contiguity Conquest... resulting in... partial state collapse "near abroad" cut off from capital Target Province Agent Province j* i

  14. Geopolitical sample run: Time = 0 Time = 1000

  15. Sample run with “tags”: Time = 0 Time = 1000

  16. Sample run with alliances: Time = 12 Time = 1000

  17. Sample run with collective security Time = 76 Time = 1000

  18. Share of democracies at t=1000

  19. Conclusions from DP-Model • It is indeed possible to “grow” the democratic peace in a Hobbesian world • All three Kantian mechanisms contribute to the democratic peace • Spatial context crucial for cooperation • But tagging does not always suffice • Counter-intuitive finding: democracy may undermine itself

  20. Four types of validation Object of validation: End point Process Mode of validation: Qualitative Distribu- tional

  21. The limits of ABM? ad hoc assumptions failure to yield predictions fragility of results lack of cumulation

  22. General readings on agent-based modeling • Axelrod, Robert. 1997. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton: Princeton University Press. • Casti, John L. 1997. Would-Be Worlds: How Simulation Is Changing the Frontiers of Science. New York: Wiley. • Cederman, Lars-Erik. 1997. Emergent Actors in World Politics: How States and Nations Develop and Dissolve. Princeton: Princeton University Press. • Epstein, Joshua M. and Robert Axtell. 1996. Growing Artificial Societies: Social Science From the Bottom Up. Cambridge, Mass.: MIT Press. • Holland, John H. 1995. Hidden Order: How Adaptation Builds Complexity. Reading, Mass.: Addison-Wesley. • Special issue on “Computational Modeling”, The Political Methodologist, Fall 2001. • See also web pages http://www.courses.fas.harvard.edu/~gov2015 and http://www.courses.fas.harvard.edu/~gov2016

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