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“Everything They Ever Wanted”: ANetLogo Case Study of a Model of Rebellion in the Tobacco Dark Patch ofTennessee and Kentucky
Unformatted Document Text:  Christopher Newman Midwest Political Science Association 2004 Elgin Community College Dark Tobacco Patch War—Revolution Analysis 17 through death, imprisonment, disillusion, maturity or boredom.) 80 If more people fall away from the revolution than join it, it will either fizzle out or be stillborn, as may be appropriate. Indeed, the original model of the NetLogo version of revolution—Rebel 1— was adapted from the Virus model 81 derived in biology. NetLogo 82 is an example of agent-based modeling. In such computer modeling, a collection of entities (“agents”) are given certain qualities and rules of behavior and set in an environment with defined characteristics as individuals. The experimenter then sits back and observes what happens. “[F]undamental social structures and group behaviors emerge from the interaction of individual agents operating on artificial environments under rules that place only bounded demands on each agent’s information and computational capacity.” [emphasis in original] 83 Agent-based modeling allows the investigator to examine problems which are not well-defined, whether because of incomplete information, or the uncertainties inherent in any human activity, or in any situation with “…complex and poorly defined problem areas.” 84 Agent-based modeling observes the actions and attributes of individuals through time, rather than averaging the characteristics of an entire population and tracking the collective activity as a unit. 85 80 Manfred Schroeder, Fractals, Chaos, Power Laws. (New York: W. H. Freeman and Company, 1991) [hereinafter “Power Laws”] 345-346. 81 Uri Wilensky, (1998). NetLogo Virus model. http://ccl.northwestern.edu/netlogo/models/Virus. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. 82 NetLogo Home. 83 Growing Artificial Societies 4-6. 84 Andrew Finegan, “Soft Systems Methodology: An Alternative Approach to Knowledge Elicitation in Complex and Poorly Defined Systems.” Complexity International 1http://www.csu.edu.au?ci/vol01/finega01/html/. 85 Craig Reynolds, “Individual-Based Models: An Annotated List of Links.” http://www.red3d.com/cwr/ibm.html.

Authors: Newman, Christopher.
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Christopher Newman Midwest Political Science Association 2004
Elgin Community College Dark Tobacco Patch War—Revolution Analysis
17
through death, imprisonment, disillusion, maturity or boredom.)
80
If more people fall
away from the revolution than join it, it will either fizzle out or be stillborn, as may be
appropriate. Indeed, the original model of the NetLogo version of revolution—Rebel 1—
was adapted from the Virus model
81
derived in biology.
NetLogo
82
is an example of agent-based modeling. In such computer modeling, a
collection of entities (“agents”) are given certain qualities and rules of behavior and set in
an environment with defined characteristics as individuals. The experimenter then sits
back and observes what happens. “[F]undamental social structures and group behaviors
emerge from the interaction of individual agents operating on artificial environments
under rules that place only bounded demands on each agent’s information and
computational capacity.” [emphasis in original]
83
Agent-based modeling allows the
investigator to examine problems which are not well-defined, whether because of
incomplete information, or the uncertainties inherent in any human activity, or in any
situation with “…complex and poorly defined problem areas.”
84
Agent-based modeling
observes the actions and attributes of individuals through time, rather than averaging the
characteristics of an entire population and tracking the collective activity as a unit.
85
80
Manfred Schroeder, Fractals, Chaos, Power Laws. (New York: W. H. Freeman and
Company, 1991) [hereinafter “Power Laws”] 345-346.
81
Uri Wilensky, (1998). NetLogo Virus model.
http://ccl.northwestern.edu/netlogo/models/Virus. Center for Connected Learning and
Computer-Based Modeling, Northwestern University, Evanston, IL.
82
NetLogo Home.
83
Growing Artificial Societies 4-6.
84
Andrew Finegan, “Soft Systems Methodology: An Alternative Approach to Knowledge
Elicitation in Complex and Poorly Defined Systems.” Complexity International 1
http://www.csu.edu.au?ci/vol01/finega01/html/.
85
Craig Reynolds, “Individual-Based Models: An Annotated List of Links.”
http://www.red3d.com/cwr/ibm.html.


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