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This book emerged out of international conferences organized as
part of the AAAI Fall Symposia series, and the Swarmfest 2017
conference. It brings together researchers from diverse fields
studying these complex systems using CAS and agent-based modeling
tools and techniques. In the past, the knowledge gained in each
domain has largely remained exclusive to that domain. By bringing
together scholars who study these phenomena, the book takes
knowledge from one domain to provide insight into others. Most
interesting phenomena in natural and social systems include
constant transitions and oscillations among their various phases -
wars, companies, societies, markets, and humans rarely stay in a
stable, predictable state for long. Randomness, power laws, and
human behavior ensure that the future is both unknown and
challenging. How do events unfold? When do they take hold? Why do
some initial events cause an avalanche while others do not? What
characterizes these events? What are the thresholds that
differentiate a sea change from a non-event? Complex adaptive
systems (CAS) have proven to be a powerful tool for exploring these
and other related phenomena. The authors characterize a general CAS
model as having a large number of self-similar agents that: 1)
utilize one or more levels of feedback; 2) exhibit emergent
properties and self-organization; and 3) produce non-linear dynamic
behavior. Advances in modeling and computing technology have led
not only to a deeper understanding of complex systems in many
areas, but they have also raised the possibility that similar
fundamental principles may be at work across these systems, even
though the underlying principles may manifest themselves
differently.
This volume spans a wide range of technical disciplines and
technologies, including complex systems, biomedical engineering,
electrical engineering, energy, telecommunications, mechanical
engineering, civil engineering, and computer science. The papers
included in this volume were presented at the International
Symposium on Innovative and Interdisciplinary Applications of
Advanced Technologies (IAT), held in Neum, Bosnia and Herzegovina
on June 26 and 27, 2016. This highly interdisciplinary volume is
devoted to various aspects and types of systems. Systems thinking
is crucial for successfully building and understanding man-made,
natural, and social systems.
This book emerged out of a project initiated and funded by the
Defense Advanced Research Projects Agency (DARPA) that sought to
build on efforts to transform agent-based models into platforms for
predicting and evaluating policy responses to real world challenges
around the world. It began with the observation that social science
theories of human behavior are often used to estimate the
consequences of alternative policy responses to important issues
and challenges. However, alternative theories that remain subject
to contradictory claims are ill suited to inform policy. The vision
behind the DARPA project was to mine the social sciences literature
for alternative theories of human behavior, and then formalize,
instantiate, and integrate them within the context of an
agent-based modeling system. The research team developed an
experimental platform to evaluate the conditions under which
alternative theories and groups of theories applied. The end result
was a proof of concept developed from the ground up of social
knowledge that could be used as an informative guide for policy
analysis. This book describes in detail the process of designing
and implementing a pilot system that helped DARPA assess the
feasibility of a computational social science project on a large
scale.
This book emerged out of a project initiated and funded by the
Defense Advanced Research Projects Agency (DARPA) that sought to
build on efforts to transform agent-based models into platforms for
predicting and evaluating policy responses to real world challenges
around the world. It began with the observation that social science
theories of human behavior are often used to estimate the
consequences of alternative policy responses to important issues
and challenges. However, alternative theories that remain subject
to contradictory claims are ill suited to inform policy. The vision
behind the DARPA project was to mine the social sciences literature
for alternative theories of human behavior, and then formalize,
instantiate, and integrate them within the context of an
agent-based modeling system. The research team developed an
experimental platform to evaluate the conditions under which
alternative theories and groups of theories applied. The end result
was a proof of concept developed from the ground up of social
knowledge that could be used as an informative guide for policy
analysis. This book describes in detail the process of designing
and implementing a pilot system that helped DARPA assess the
feasibility of a computational social science project on a large
scale.
Questions of values, ontologies, ethics, aesthetics, discourse,
origins, language, literature, and meaning do not lend themselves
readily, or traditionally, to equations, probabilities, and models.
However, with the increased adoption of natural science tools in
economics, anthropology, and political science to name only a few
social scientific fields highlighted in this volume quantitative
methods in the humanities are becoming more common.
The theory of complexity holds significant promise for better
understanding social and human phenomena based on interactions
among the participating "agents," whatever they may be: a thought,
a person, a conversation, a sentence, or an email. Such systems can
exhibit phase transitions, feedback loops, self-organization, and
emergent properties. These dynamic systems lend themselves
naturally to the kind of analysis made possible by models and
simulations developed with complex science tools. This volume
offers a tour of quantitative analyses, models, and simulations of
humanities and social science phenomena that have been historically
the purview of qualitative methods. "
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