Agents, Networks, Evolution: A Quarter Century of Advances in Complex Systems

612 Pages·2022·43.916 MB·English

by  Frank Schweitzer

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Agents
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Recommended Titles in Related Topics
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m ISBN: 978-981-3239-59-3
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Agents
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Evolution
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Frank Schweitzer
ETH Zürich, Switzerland
World Scientific
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Library of Congress Control Number: 2022946214
British Library Cataloguing-in-Publication Data
A catalogue record for this book is available from the British Library.
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For photocopying of material in this volume, please pay a copying fee through the Copyright Clearance Center,
Inc., 222 Rosewood Drive, Danvers, MA 01923, USA. In this case permission to photocopy is not required from
the publisher.
ISBN 978-981-126-781-9 (hardcover)
ISBN 978-981-126-782-6 (ebook for institutions)
ISBN 978-981-126-783-3 (ebook for individuals)
For any available supplementary material, please visit
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August26,2022 14:14 ws-book961x669-modified-961x669 AQuarterCenturyofAdvancesinComplexSystems book-ACS25 pagev
Preface
A lot has happened over the last 25 years in the scientific quest for a systematic
understanding of complex systems. Complexity science has gradually transitioned
from a stage dominated by conceptualization, exploration in simple models, and
theory at the turn of the millennium, to a truly empirical endeavor tackling science’s
deepest questions – a science as it ought to be: quantitative, predictive, and testable.
A quarter-century ago, the concepts of evolutionary dynamics, adaptation, emer-
gence, co-evolution, networks, agent-based models, self-organization, scaling, hyper-
graphs, or artificial life – all seemed to have been at their infancy. Similarly, the
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statistics of strongly correlated systems, the physics of small stochastic systems, the
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ntifi were practically non-existent. Networks just started to enter the scene, expanding
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s early applications in sociology and geography. Some highlights from that time were
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m models. Most of the complexity science then relied heavily on conceptualization and
d fro theory applied to toy models and was far from being “useful” in real systems. It
e consisted of many loosely connected interesting bits and pieces and it was unclear
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systems: How should it ever be possible to treat heavily interconnected systems that
have co-evolving boundaries, are non-linear, non-ergodic, non-separable, that are
driven and out of equilibrium? In short, complexity scientists were interested in
exotic problems that a mainstream scientist would never touch.
The crucial game changer over the past two decades was the explosion of data.
Because of underlying technological trends, many different kinds of data quickly
becamelargeandpervasiveformanydifferentcomplexsystems,suchassocial,living,
ecological, medical, traffic, urban, economic, financial, and climate systems. In more
and more cases, relevant “big” data about the structure and dynamics of any given
system has becomes available at high resolution and with high accuracy.
The fast expansion of data forced all fields dealing with complex systems to
operate differently, engaging anew with questions of heterogeneity, inequality, non-
linear interactions and collective organization. The time was then ripe for the
convergence of bigger and better data with the concepts developed all along by
complexity science. Novel modeling techniques, network and hypergraph methods,
new mathematical analysis tools and more appropriate statistics, finally became
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August26,2022 14:14 ws-book961x669-modified-961x669 AQuarterCenturyofAdvancesinComplexSystems book-ACS25 pagevi
vi A Quarter Century of Advances in Complex Systems
not only useful but necessary. This convergence also created new possibilities for
putting complexity science to the test, and for its fast development in interaction of
appropriate evidence closing the loop of the scientific method for the first time in
many complex systems. In other words, we currently see many areas of complexity
science turning into an empirical science that is effectively testable and that allows
ustocalibratehigherdimensionalmodelswithdatafromrealandimportantsystems.
This empirical progress in turn tremendously accelerates the development towards
a “useful” science in the sense that it helps us better understand the complexity
around us and maybe – for the first time – manage it on scientific grounds. This
practical potential and some remarkable successes became obvious during the recent
COVID-19 pandemic, when many complexity scientists played an active role all over
the world.
This success of complexity science over the past 25 years would not have been
possiblewithoutpioneeringinstitutions, liketheSantaFeInstitute, orjournals, such
as the Advances of Complex Systems (ACS). These pioneering venues provided the
m fora for communication, coordination, selection of ideas and cooperation between
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ntifi history and the remarkable transformation of complexity science over time. This is
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w. Systemspresentsacomprehensiveoverviewofsomeofthemostrelevantdevelopments
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ed fr central tools of linking microscopic update dynamics with systemic (system-wide)
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(3)systemdynamics,whichcoversbiologicalphenomena,traffic,ecosystems,climate,
and disease spreading, and, finally, (4) evolutionary dynamics, a chapter that spans
a range of questions from replicator dynamics to the tremendous challenge of co-
evolution, a topic that is still far from being fully understood.
All four chapters start with an overview of the topical areas by Frank Schweitzer,
theEditorinChiefandthedrivingforcebehindACSformanyyears. Theseinsightful
introductions make the book more accessible to non-experts, a fact that should help
to spread recent developments in complexity science also to a younger audience and
scientists outside the field. Experts will enjoy (re-)reading the contributions of a
selected crowd of renown complexity scientists. Finally, the book takes an explicit
focus on a number of concrete applications in different scientific areas, which makes
itparticularlyattractive asitgivesaglimpse ofwhat the scienceofcomplexsystems
might bring to how we fundamentally understand and manage our societies and
natural environments in the decades ahead.
Stefan Thurner, Complexity Science Hub Vienna & Santa Fe Institute
Lu´ıs M. A. Bettencourt, University of Chicago & Santa Fe Institute
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Contents
Preface v
1. Frank Schweitzer: Introduction 1
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5. Dirk Helbing, Martin Sch¨onhof, Hans-Ulrich Stark and Janusz
A. Ho(cid:32)lyst: How Individuals Learn to Take Turns: Emergence of
AlternatingCooperationinaCongestionGameandthePrisoner’s
Dilemma 60
6. Floriana Gargiulo, Yerali Gandica and Timoteo Carletti: Emer-
gent Dense Suburbs in a Schelling Metapopulation Model: A
Simulation Approach 90
7. Alessandro Pluchino, Alessio Emanuele Biondo and Andrea Rapis-
arda: Talent Versus Luck: The Role of Randomness in Success
and Failure 107
8. Frank Schweitzer, Antonios Garas, Mario V. Tomasello, Giacomo
Vaccario and Luca Verginer: The Role of Network Embeddedness
ontheSelectionofCollaborationPartners: AnAgent-BasedModel
with Empirical Validation 138
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viii A Quarter Century of Advances in Complex Systems
Network Models 157
9. Frank Schweitzer: Overview 159
10. Marc Barth´elemy, Alain Barrat and Alessandro Vespignani: The
Role of Geography and Traffic in the Structure of Complex
Networks 174
11. Franceso Pozzi, Tiziana Di Matteo and Tomaso Aste: Centrality
and Peripherality in Filtered Graphs from Dynamical Financial
Correlations 198
12. Luiz H. Gomes, Virgilio A. F. Almeida, Jussara M. Almeida,
Fernando D. O. Castro and Lu´ıs M. A. Bettencourt: Quantifying
m Social and Opportunistic Behavior in Email Networks 222
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P´adraig Maccarron: Detecting Opinion-Based Groups and Po-
larization in Survey-Based Attitude Networks and Estimating
Question Relevance 278
System Dynamics Models 315
16. Frank Schweitzer: Overview 317
17. Andrew J. Spencer, Iain D. Couzin and Nigel R. Franks: The
Dynamics of Specialization and Generalization within Biological
Populations 334
18. A. J. Palmer, T. L. Schneider and L. A. Benjamin: Inference
Versus Imprint in Climate Modeling 347
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A Quarter Century of Advances in Complex Systems ix
19. Robin C. Ball, Marina Diakonova and Robert S. Mackay: Quanti-
fying Emergence in Terms of Persistent Mutual Information 364
20. Jianjun Wu, Mingtao Xu and Ziyou Gao: Modeling the Coevolu-
tion of Road Expansion and Urban Traffic Growth 376
21. Hugo C. Mendes, Alberto Murta and R. Vilela Mendes: Long
Range Dependence and the Dynamics of Exploited Fish
Populations 394
22. Inga Ivanova, Øivind Strand and Loet Leydesdorff: An Eco-
Systems Approach to Constructing Economic Complexity Mea-
sures: Endogenization of the Technological Dimension Using
Lotka–Volterra Equations 408
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ntific. plitude Dynamics Underlying Covid-19 Outbreaks in China 429
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26. Werner Ebeling, Karmeshu and Andrea Scharnhorst: Dynam-
ics of Economic and Technological Search Processes in Complex
Adaptive Landscapes 492
27. Ba¨rbel M. R. Stadler and Peter F. Stadler: Molecular Replicator
Dynamics 510
28. Christoph Hauert: Cooperation, Collectives Formation and
Specialization 541
29. Stephanie Keller-Schmidt and Konstantin Klemm: A Model of
Macroevolution as a Branching Process Based on Innovations 562
30. Malte Harder and Daniel Polani: Self-Organizing Particle Systems 578