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research tools & methods
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summer 2018 â—Ľ options
T he “fog of war” and Donald
Rumsfeld’s “unknown unknowns”
in Iraq in 2002, are quotes often
used by military strategists and
authors to convey the uncertainty
surrounding military operations. It is perhaps
understandable that those seeking to end
conflict, or indeed pursue it, might turn to
mathematical modeling for clarity.
In the recent paper, “Conflicts among
N armed groups: Scenarios from a new
descriptive model,” Sergio Rinaldi and Fabio
Della Rossa propose and analyze a model
that describes armed conflict between a
government group and one or two rebel
groups. Rinaldi, a researcher at IIASA, says that
a scarcity of reliable data has led to the belief
that the outcome of such complex conflicts
cannot be predicted. But what happens if the
data is comprehensive and trustworthy?
The model reveals that the dynamics
among fighting groups can be extremely
sensitive to the conflict’s initial conditions
and parameter values. “This suggests that
a conflict’s outcome may be practically
unpredictable, even if very rich data sets were
available,” says Rinaldi. He adds that this might
be an uncomfortable truth for strategists who are increasingly turning to dynamic modeling
to disperse some of that “fog of war.”
“Rebels cannot be
eradicated if they are highly
fanatical” – Sergio Rinaldi
For the modeled conflict, some interesting
properties emerged. Government groups,
if highly defensive, cannot go extinct, while
their rebel opponents cannot be eradicated if
they are highly fanatical. Instead, stalemates
arise and when a conflict is caught in a
turbulent stalemate, “the model allows one to
determine when a short military intervention
of an allied country should be performed to
have the highest chances of eradicating the
enemies,” conclude the researchers.
Rinaldi and Della Rossa caution that their
results are preliminary and that more subtle
considerations–such as the existence of chaotic
regimes and the systematic evaluation of the
role of strategic factors like power, intelligence,
and fanaticism–remain open and require
further research. The many failed attempts
to resolve drawn-out contemporary conflicts
would seem to support their conclusions. KS
Mathematical models and armed
conflict–A case for caution
Armed conflicts are widespread and yet their dynamics are poorly understood. A simple
model can enable insights into the potential for stalemates and a conflict’s ultimate outcome.
Further info Rinaldi S, Della Rossa F (2018). Conflicts
among N armed groups: Scenarios from a new
descriptive model. Nonlinear Dynamics 92: 3-12:
[pure.iiasa.ac.at/14368]
Sergio Rinaldi rinaldi@iiasa.ac.at
Understanding terrorist organizations
and responses
In their paper “Differential Terror Queue
Games”, IIASA researchers describe
applying game-theoretic modeling to
terrorist strategies and government
responses. In these games, terrorists seek
optimal attack rates, while the government
simultaneously develops optimal counter-
terror staffing levels. The researchers
describe circumstances in which terror
groups will either increase or decrease their
attacks, for example, “they will attack less
as they know that by planning terror plots
they will strongly provoke counteractions.”
The research aims to build on a growing
body of academic literature on dealing
with terrorism.
Further info Wrzaczek S, Kaplan EH, Caulkins JP,
Seidl A, & Feichtinger G (2017). Differential Terror
Queue Games. Dynamic Games and Applications 7 (4):
578-593. [pure.iiasa.ac.at/13857]
Gustav Feichtinger feichtin@iiasa.ac.at
iiasa research
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Volume summer 2018
- Title
- options
- Volume
- summer 2018
- Location
- Laxenburg
- Date
- 2018
- Language
- English
- License
- CC BY-NC 4.0
- Size
- 21.0 x 29.7 cm
- Pages
- 28
- Categories
- Zeitschriften Options Magazine