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*_Notice and Invitation_*
Oral Defense of Doctoral Dissertation
The Volgenau School of Engineering, George Mason University

Kenneth W. Comer
Bachelor of Arts, Cornell University, 1974
Master of Arts, Georgetown University, 1983
Master of Science, The George Washington University, 1989

  

*Who Goes First?
An Examination of the Impact of Activation on Outcome Behavior
in Applied Agent-based Models*

Monday, March 10, 2014, 10:00AM - Noon
Room 2901

Nguyen Engineering Building

All are invited to attend.

*_Committee_*
Dr. Andrew G. Loerch, Chair
Dr. Chun-Hung Chen

Dr. Rajesh Ganesan

Dr. Robert Axtell


_Abstract_

Agent-based models have become the tool of choice for modeling 
self-organizing systems. In fact, for some domains they have supplanted 
traditional discrete event simulations as decision-support elements to 
explore the potential outcome space. In creating a specific agent-based 
model, there are several choices the simulation designer must make. 
Often these design decisions are implicit, but they may be important in 
the performance of the simulation. One such choice is the sequence with 
which the agents will execute their methods or change their state. This 
is the 'activation' question, and its impact on three different models 
is examined in this dissertation.

  Three agent-based models described in the literature in three separate 
domains (civil unrest, market execution, and social interactions) were 
replicated, and the impact of various activation schemes on the emergent 
population patterns and dynamics was analyzed. It was demonstrated that 
the choice of activation type is important for the outcome behavior of 
the model and should be stipulated in any published description of an 
agent-based model. In some experiments the differences noted, while 
significant, were only statistical. In others they led to substantial 
differences in either outcomes or model behavior. Further investigation 
showed that sophisticated activation schemes can become powerful tools 
to produce unexpected or unpredicted behavior of multi-agent systems. 
Thus, activation becomes more than an inconvenient detail to be dealt 
with during design, and is shown to be a source of exploratory variation 
as modelers of self-organizing social systems seek to match the behavior 
of natural systems.

A copy of this doctoral dissertation is on reserve at the Johnson Center 
Library.