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Books > Business & Economics > Economics > Econometrics
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Agent-Based Modeling and Network Dynamics (Hardcover)
Loot Price: R2,938
Discovery Miles 29 380
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Agent-Based Modeling and Network Dynamics (Hardcover)
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Donate to Against Period Poverty
Total price: R2,958
Discovery Miles: 29 580
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While the significance of networks in various human behavior and
activities has a history as long as human's existence, network
awareness is a recent scientific phenomenon. The neologism network
science is just one or two decades old. Nevertheless, with this
limited time, network thinking has substantially reshaped the
recent development in economics, and almost all solutions to
real-world problems involve the network element. This book
integrates agent-based modeling and network science. It is divided
into three parts, namely, foundations, primary dynamics on and of
social networks, and applications. The authors begin with the
network origin of agent-based models, known as cellular automata,
and introduce a number of classic models, such as Schelling's
segregation model and Axelrod's spatial game. The essence of the
foundation part is the network-based agent-based models in which
agents follow network-based decision rules. Under the influence of
the substantial progress in network science in late 1990s, these
models have been extended from using lattices into using
small-world networks, scale-free networks, etc. The text also shows
that the modern network science mainly driven by game-theorists and
sociophysicists has inspired agent-based social scientists to
develop alternative formation algorithms, known as agent-based
social networks. It reviews a number of pioneering and
representative models in this family. Upon the given foundation,
the second part reviews three primary forms of network dynamics,
such as diffusions, cascades, and influences. These primary
dynamics are further extended and enriched by practical networks in
goods-and-service markets, labor markets, and international trade.
At the end, the book considers two challenging issues using
agent-based models of networks: network risks and economic growth.
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