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Militarized Conflict Modeling Using Computational Intelligence (Hardcover, 2011 ed.)
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Militarized Conflict Modeling Using Computational Intelligence (Hardcover, 2011 ed.)
Series: Advanced Information and Knowledge Processing
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Militarized Conflict Modeling Using Computational Intelligence
examines the application of computational intelligence methods to
model conflict. Traditionally, conflict has been modeled using game
theory. The inherent limitation of game theory when dealing with
more than three players in a game is the main motivation for the
application of computational intelligence in modeling conflict.
Militarized interstate disputes (MIDs) are defined as a set of
interactions between, or among, states that can result in the
display, threat or actual use of military force in an explicit way.
These interactions can result in either peace or conflict. This
book models the relationship between key variables and the risk of
conflict between two countries. The variables include Allies which
measures the presence or absence of military alliance, Contiguity
which measures whether the countries share a common boundary or not
and Major Power which measures whether either or both states are a
major power. Militarized Conflict Modeling Using Computational
Intelligence implements various multi-layer perception neural
networks, Bayesian networks, support vector machines, neuro-fuzzy
models, rough sets models, neuro-rough sets models and optimized
rough sets models to create models that estimate the risk of
conflict given the variables. Secondly, these models are used to
study the sensitivity of each variable to conflict. Furthermore, a
framework on how these models can be used to control the
possibility of peace is proposed. Finally, new and emerging topics
on modelling conflict are identified and further work is proposed.
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