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This book provides a state-of-the-art overview on the dynamics and
coevolution in multi-level strategic interaction games. As such it
summarizes the results of the European CONGAS project, which
developed new mathematical models and tools for the analysis,
prediction and control of dynamical processes in systems possessing
a rich multi-level structure and a web of interwoven interactions
among elements with autonomous decision-making capabilities. The
framework is built around game theoretical concepts, in particular
evolutionary and multi-resolution games, and includes also
techniques drawn from graph theory, statistical mechanics, control
and optimization theory. Specific attention is devoted to systems
that are prone to intermittency and catastrophic events due to the
effect of collective dynamics.
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Algorithms and Models for the Web Graph - 16th International Workshop, WAW 2019, Brisbane, QLD, Australia, July 6-7, 2019, Proceedings (Paperback, 1st ed. 2019)
Konstantin Avrachenkov, Pawel Pralat, Nan Ye
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R1,557
Discovery Miles 15 570
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Ships in 10 - 15 working days
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This book constitutes the proceedings of the 16th International
Workshop on Algorithms and Models for the Web Graph, WAW 2019, held
in Brisbane, QLD, Australia, in July 2019. The 9 full papers
presented in this volume were carefully reviewed and selected from
13 submissions. The papers cover topics of all aspects of
algorithmic and mathematical research in the areas pertaining to
the World Wide Web, espousing the view of complex data as networks.
This book provides a state-of-the-art overview on the dynamics and
coevolution in multi-level strategic interaction games. As such it
summarizes the results of the European CONGAS project, which
developed new mathematical models and tools for the analysis,
prediction and control of dynamical processes in systems possessing
a rich multi-level structure and a web of interwoven interactions
among elements with autonomous decision-making capabilities. The
framework is built around game theoretical concepts, in particular
evolutionary and multi-resolution games, and includes also
techniques drawn from graph theory, statistical mechanics, control
and optimization theory. Specific attention is devoted to systems
that are prone to intermittency and catastrophic events due to the
effect of collective dynamics.
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Game Theory for Networks - 8th International EAI Conference, GameNets 2019, Paris, France, April 25-26, 2019, Proceedings (Paperback, 1st ed. 2019)
Konstantin Avrachenkov, Longbo Huang, Jason R. Marden, Marceau Coupechoux, Anastasios Giovanidis
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R1,684
Discovery Miles 16 840
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 8th EAI
International Conference on Game Theory for Networks, GameNets
2019, held in Paris, France, in April 2019. The 8 full and 3 short
papers presented were carefully reviewed and selected from 17
submissions. They are organized in the following topical sections:
Game Theory for Wireless Networks; Games for Economy and Resource
Allocation; and Game Theory for Social Networks.
This book is a general introduction to the statistical analysis of
networks, and can serve both as a research monograph and as a
textbook. Numerous fundamental tools and concepts needed for the
analysis of networks are presented, such as network modeling,
community detection, graph-based semi-supervised learning and
sampling in networks. The description of these concepts is
self-contained, with both theoretical justifications and
applications provided for the presented algorithms.Researchers,
including postgraduate students, working in the area of network
science, complex network analysis, or social network analysis, will
find up-to-date statistical methods relevant to their research
tasks. This book can also serve as textbook material for courses
related to thestatistical approach to the analysis of complex
networks.In general, the chapters are fairly independent and
self-supporting, and the book could be used for course composition
"a la carte". Nevertheless, Chapter 2 is needed to a certain degree
for all parts of the book. It is also recommended to read Chapter 4
before reading Chapters 5 and 6, but this is not absolutely
necessary. Reading Chapter 3 can also be helpful before reading
Chapters 5 and 7. As prerequisites for reading this book, a basic
knowledge in probability, linear algebra and elementary notions of
graph theory is advised. Appendices describing required notions
from the above mentioned disciplines have been added to help
readers gain further understanding.
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Discovery Miles 3 300
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