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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

ABM Applications to the Social Sciences

Lars-Erik Cederman

Department of Government, Harvard

EITM Workshop, July 18, 2002


Outline applications
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


Three types of emergent effects

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


Barabasi s preferential attachment model
Barabasi’s Preferential Attachment Model

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


Applications to political science
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


Modeling the democratic peace with agent based modeling
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).


Outline
Outline

1. Modeling geopolitics

2. Adding tags

3. Adding alliances

4. Adding collective security

5. Replications

6. Conclusions


Modeling geopolitics geosim
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



Tagged decision rule for democratic state i
“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*


Threshold functions
Threshold functions

Probability

Decision to

attack

p(i,j*)

Combat

victory

Force ratio


Structural change conquest
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


Guaranteeing territorial contiguity
Guaranteeing territorial contiguity

Conquest... resulting in... partial state collapse

"near abroad"

cut off from

capital

Target

Province

Agent

Province

j*

i


Geopolitical sample run
Geopolitical sample run:

Time = 0

Time = 1000


Sample run with tags
Sample run with “tags”:

Time = 0

Time = 1000


Sample run with alliances
Sample run with alliances:

Time = 12

Time = 1000




Conclusions from dp model
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


Four types of validation
Four types of validation

Object of validation:

End point Process

Mode of

validation:

Qualitative

Distribu-

tional


The limits of abm
The limits of ABM?

ad hoc assumptions

failure to yield predictions

fragility of results

lack of cumulation


General readings on agent based modeling
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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