What might be inferred from the observation by Craig Reynolds that
"a flock is not a big bird"?
Distinguishing between "simple" and "complex" economic systems -- what
role do network effects play?
Under what circumstances can robust point predictions of economic
outcomes be obtained from a knowledge of initial economic structure,
ignoring network effects? And when might network
effects be important for the prediction of economic outcomes?
Is the global economy becoming strongly interactive? If so, is this a
good thing?
How can graph theory be used to quantitatively represent and analyze
economic interaction networks?
What type of systematic phase transition do random graphs undergo as
their connectivity increases?
Do socioeconomic networks exhibit any kind of systematic phase transition
as their connectivity increases?
Why all the recent excitement about "small-world networks"
(locally dense networks with global reach)?
Is economic interaction a catalyst for economic change?
In particular, do economic networks exhibit "autocatalytic" properties?
How do agents learn in networks? Does learning through interaction
necessarily promote cooperation?
Frédéric Amblard, "Simulating Social Networks: A Review of
Three Books"(html,7pp),
Journal of Artificial Societies and Social Simulation (JASSS), Vol. 6,
No. 2, March 2003 (electronic journal).
Abstract: Amblard reviews Duncan Watts' Small
Worlds... (1999), Albert-Lázló Barabási's
Linked (2002), and Mark Buchanan's Nexus... (2002).
David F. Batten, Chapter 3: "Sheeps, Explorers, and Phase Transitions" and
Chapter 4:"The Ancient Art of Learning by Circulating",
in Discovering Artificial Economics: How Agents Learn and Economies Evolve, Perseus Books, Westview Press, 2000.
See also L. Tesfatsion, "Notes on Network Effects (Batten Chapter 3 Plus Glossary of Terms)"(html)
and "Notes on Learning in Networks (Batten Chapter 4 Plus Glossary of Terms)"(html).
Note: Unfortunately the Batten book is now out of print. However, the entire Batten book
(figures included) in pdf can be accessed at
here (pdf,17MB).
Giorgio Fagiolo (Laboratory of Economics and Management, Sant'Anna School of Advanced studies, Pisa, Italy) has prepared a ppt presentation, titled
Games on Networks: Rationality, Dynamics, and Interactions (pdf,1.5MB),
that reviews recent research by himself and others on the endogenous formation of networks by strategically interacting players in a variety of application contexts.
Leigh Tesfatsion, "Presentation Slides on the Structural and Dynamical Analysis of Networks"(pdf,2.3MB)
and
"Lecture Notes on Networks"(html).
Abstract: These presentation slides and lecture notes provide rigorous definitions for basic structural characterizations of networks (e.g., degree, clustering, shortest path length). Also discussed are phase transitions in random graphs, the concept of a "small world network," and the possible application of small-world networks to the study of trade interactions.
Leigh Tesfatsion, "Introductory Notes on Network Formation"(pdf,246KB).
Leigh Tesfatsion, "Endogenous Determination of Trade Networks: An Illustrative Labor Market Application"(pdf,117KB).
Allen Wilhite, "Bilateral Trade and `Small-World' Networks"(pdf,181KB),
Computational Economics, Vol. 18, No. 1, August 2001, pp. 49-64. The published article is available at
SpringerLink.
See also Leigh Tesfatsion, "Notes on Wilhite (2001)"(pdf,236KB).
Abstract: Wilhite develops an agent-based
computational model of a bilateral exchange economy in which profit-seeking traders sequentially engage in
trade partner search, negotiation, and trading. He uses this model to
explore the consequences of restricting trade to different types of networks,
including a "small-world network" with both local connectivity and global
reach. His key finding is that small-world networks provide most of the
market-efficiency advantages of completely connected networks while retaining
almost all of the transaction cost economies of locally connected networks.
Allen W. Wilhite,
"Economic Activity on Fixed Networks",
in Leigh Tesfatsion and Kenneth L. Judd (editors),
Handbook of Computational Economics, Vol. 2: Agent-Based Computational
Economics, Handbooks in Economics Series, North-Holland/Elsevier, Amsterdam,
Spring 2006.
Abstract:
"A large portion of our economic interactions involves a very
small portion of the population. We seem to prefer familiar venues.
But the tendency to focus our attention on a few individuals or
activities is an attribute that is typically omitted in our
characterization of markets. In markets, agents seem to interact
impersonally and efficiently with countless other faceless agents.
This chapter looks into the consequences of including a connection
between agents, a tendency to interact with a specific few, in
economic decision-making. Agents are assumed to occupy the nodes of
a network and to interact exclusively with agents to whom they are
directly linked. We then study evolution of game strategies and the
effectiveness of exchange as the topology of the underlying network
is altered. We find that networks matter, that changes in a
network's structure can alter the steady-state attributes of an
artificial society as well as the dynamics of that system."
Nicolaas J. Vriend,
"ACE Models of Endogenous Interactions",
in Leigh Tesfatsion and Kenneth L. Judd (editors),
Handbook of Computational Economics, Vol. 2: Agent-Based Computational
Economics, Handbooks in Economics Series, North-Holland/Elsevier, Amsterdam,
Spring 2006.
Abstract:
Various approaches used in Agent-based Computational Economics
(ACE) to model endogenously determined interactions between agents
are discussed. This concerns models in which agents not only learn
how to play games, but also how agents learn to decide
with whom to play or not.
Janette Aschenwald, Stefan Fink, and Gottfied Tappeiner, "Brave New
Modeling: Cellular Automata and Artificial Neural Networks for Mastering
Complexity in Economics,"Complexity
7(1), 2002, 39-47.
Albert-László Barabási, Linked: The New Science of Networks, Perseus Publisher, May 2002. ISBN: 0-738-20667-9.
Abstract: "In Linked,
Barabasi, a physicist whose work has revolutionized the study of networks,
traces the development of this rapidly unfolding science and introduces us to
the scientists carrying out this pioneering work. These `new cartographers'
are mapping networks in a wide range of scientific disciplines, proving that
social networks, corporations, and cells are more similar than they are
different, and providing important new insights into the interconnected world
around us. This knowledge, says Barabasi, can shed light on the robustness
of the Internet, the spread of fads and viruses, even the future of
democracy. Engaging and authoritative, Linked provides an exciting
preview of the next century in science, guaranteed to be transformed by these
amazing discoveries."
Albert-László Barabási is the Emil T. Hofman
Professor of Physics at the University of Notre Dame, South Bend, Indiana.
Sushil Bikhchandani, David Hirshleifer, and Ivo Welch, "Learning from
the Behavior of Others: Conformity, Fads, and Information Cascades,"Journal of Economic Perspectives 12(3), 1998, 151-170.
Phillip Bonacich, The Evolution of Exchange Networks(html, 21pp.),
Journal of Social Structure, Volume 2, Number 5, 2001.
Abstract: Computer simulations are used to explore how 2-dimensional spatial networks of exchange opportunities evolve. Agents are placed on a checkerboard with patched edges (a torus) in which neighboring positions can exchange with one another. Each transaction produces a profit that can be divided between the two participants if they can agree on a division. Agents change their positions (locations) in successive rounds based on a very simple win-stay/lose-change strategy: Agents do not change their position is they earn more than a certain minimum; agents whose earnings fall below the minimum randomly pick a neighboring square and move to this square if unoccupied. The computer simulations suggest that only networks with high degrees of power imbalance are unstable, and that there are three basic forms of stable networks.
Giangiacomo Bravo, Flaminio Squazzoni, and Riccardo Boero, "Trust and Partner Selection in Social Networks: An Experimentally Grounded Model"(pdf,608KB),
Social Networks, 2012, to appear.
Abstract: This article investigates the importance of the endogenous selection of partners for trust and cooperation in market exchange situations, where there is information asymmetry between investors and trustees. The authors create an experimental-data driven agent-based model where the endogenous link between interaction outcome and social structure formation is examined starting from heterogeneous agent behaviour. By testing various social structure configurations, the authors show that dynamic networks lead to more cooperation when agents can create more links and reduce exploitation opportunities by free riders. Furthermore, the authors find that endogenous network formation is more important for cooperation than the type of network per se.
Ronald Brieger, Kathleen M. Carley, and Philippa Pattison (eds.), Dynamic Social Network Modeling
and Analysis, Workshop Summary and Papers, Committee on Human Factors, Board on Behavioral,
Cognitive, and Sensory Sciences, National Academy Press, Washington, D.C., 2003.
Abstract: This volume collects together papers focusing on current
developments in the science of social network modeling, including applications in the
area of national security. Part I of this document is a summary
of major themes, together with research issues and prospects. Part II contains the papers themselves.
Mark Buchanan, Nexus: Small Worlds and the Groundbreaking Science of
Networks, W. W. Norton, New York, N.Y., 2002. ISBN: 0-393-04153-0.
Mark Buchanan holds a Ph.D. in physics and has been an editor at
Nature and New Scientist.
Giorgio Fagiolo,
"Endogenous Neighborhood Formation in a Local Coordination Model with Negative Network Externalities"(pdf,267KB),
Journal of Economic Dynamics and Control, Vol. 29, 2005, pp. 297-319.
Abstract"
The paper studies the evolution of coordination in a local interaction model where agents can
simultaneously choose the strategy to play in the game and the size of their neighborhood. We
focus on pure-coordination games played by agents located on one-dimensional lattices and we
assume that network externalities become eventually negative as neighborhood sizes increase.
We show that the society almost always converges to a steady-state characterized by high levels
of coordination and small neighborhood sizes. We find that neighborhood adjustment allows for
higher coordination than if interaction structures were static and that large populations attain
higher coordination provided that average initial neighborhood sizes are not too small.
John Foster, "From Simplistic to Complex Systems in Economics"(pdf,148KB),
Discussion Paper 335, School of Economics, University of Queensland, October
2004, published in the Cambridge Journal of Economics.
Abstract: The applicability of complex systems theory
in economics is evaluated and compared with standard approaches to economic
theorizing based upon constrained optimization... It is explained why it is
necessary to approach economic analysis from a network, rather than a
production and utility function perspective, when we are dealing with complex
systems.
Prasanna Gai, Andrew Haldane, and Sujit Kapadia, "Complexity, Concentration, and Contagion"(pdf,621KB),
Journal of Monetary Economics, Vol. 58, 2011, 453-470.
Abstract:
"This paper develops a network model of interbank lending in which unsecured claims, repo activity and shocks to the haircuts applied to collateral assume centre stage. We show how systemic liquidity crises of the kind associated with the interbank market collapse of 2007-2008 can arise within such a framework, with funding contagion spreading widely through the web of interlinkages. Our model illustrates how greater complexity and concentration in the financial network may amplify this fragility. The analysis suggests how a range of policy measures - including tougher liquidity regulation, macro-prudential policy, and surcharges for systemically important financial institutions - could make the financial system more resilient."
Alan P. Kirman and Nicolaas J. Vriend, "Evolving Market Structure: An
ACE Model of Price Dispersion and Loyalty"(pdf,443KB),
Journal of Economic Dynamics and Control, Vol. 25, Nos. 3-4, 2001, pp. 459-502
Abstract: Kirman and Vriend develop an agent-based
computational model capturing salient structural aspects of the actual
wholesale fish market in Marseilles, France. Two features characterizing
this actual market are: (a) loyalty relationships (persistent trade
partnerships) between particular buyers and sellers; and (b) persistent price
dispersion unexplainable by observable characteristics of the fish. The
simulation results show that loyalty relationships can indeed emerge
naturally between particular buyer-seller pairs as the buyers and sellers
co-evolve their trading rules over time. Buyers learn to become loyal to
particular sellers while, at the same time, sellers learn to offer higher
payoffs (lower prices and more reliable supplies) to their more loyal buyers.
Moreover, this evolving trade network supports persistent price dispersion
over time.
Dan Ladley and Seth Bullock, "The Strategic Exploitation of Limited Information
and Opportunity in Networked Markets"(pdf,468KB),
Computational Economics, Vol. 32, 2008, pp. 295-315.
Abstract: This paper studies the effect of constraining interactions within a market.
A model is analysed in which boundedly rational agents trade with and gather
information from their neighbours within a trade network. It is demonstrated that a
trader’s ability to profit and to identify the equilibrium price is positively correlated
with its degree of connectivity within the market. Where traders differ in their number
of potential trading partners, well-connected traders are found to benefit from aggressive
trading behaviour.Where information propagation is constrained by the topology
of the trade network, connectedness affects the nature of the strategies employed.
Alina Lazar, David Chavalarias, and T. K. Ahn, "Endogenous Network
Formation and the Evolution of Preferences"(pdf,370KB),
Presented at Agent2002, University of Chicago, October 11-12, 2002.
Abstract: The authors develop analytical and
computational models to study the conditions for the stability of a
population consisting of agents with heterogeneous preferences. The
analytical models that utilize an indirect evolutionary approach show that
the ability to detect others' types is critical for the evolution of
reciprocal preferences. The computational models of this paper incorporate
agents' memories and endogenously built social networks into the evolutionary
dynamics. The simulations based on the computational models show that the
strength of the social network is a critical factor for the success of
nonselfish preferences. A fully heterogeneous population consisting of
egoists, reciprocators, and altruists can be stable for a range of parameter
conditions.
M. E. J. Newman, "Models of the Small World: A Review"(pdf,202KB),
Journal of Statistical Physics 101 (2000), 819-841.
Mark Pingle and Leigh Tesfatsion, "Evolution of Worker-Employer
Networks and Behaviors Under Alternative Non-Employment Benefits: An
Agent-Based Computational Study", pp. 256-285 in Anna Nagurney (ed.),
Innovations in Financial and Economic Networks, New Dimensions in
Networks Book Series, Edward Elgar Publishers, 2003
(pdf preprint,269KB),
(pdf presentation,88KB).
Abstract:
This study replaces the standard exogenously-given worker-employer matching function with endogenous preferential worker-employer matching based on past work-site experiences. Workers and employers participate in a sequential employment game with adaptive job search and incomplete contracts. Matched workers and employers participate in a work-site game. The study examines the effects of a non-employment payoff (NEP) on network formation and work-site behaviors. Taking both utility benefits and program costs into account, the highest efficiency is achieved with a moderate NEP level. A zero NEP encourages too much shirking on the work-site, while a high NEP results in too high a risk of lost earnings due to coordination failure.
Domenico Prisi and Massimiliano Ugolini, "Living in Enclaves",
Complexity,
Volume 7, No. 1, September/October 2001.
Abstract: The authors ask: "What are the consequences
of living in small isolated communities vs living in larger environments as
members of bigger communities?" The authors use an agent-based spatial
computational framework similar to Epstein and Axtell's Sugarscape and
Holland's Echo to study populations of organisms living and reproducing
either in isolated enclaves or in a common environment. They study the role
of artifacts that increase energy extracted from natural resources in helping
these populations avoid extinction.
James E. Rauch and Alessandra Casella (eds.), Networks and
Markets, Russell Sage Foundation, New York, 2001.
Abstract:: "(This book) argues
that economists' knowledge of markets and sociologists' rich understanding of
networks can and should be combined... The book includes contributions by
both sociologists and economists, applying the concepts of markets and
networks to concrete empirical phenomena."
James E. Rauch, "Business and Social Networks in International
Trade,"Journal of Economic Literature, Volume XXXIX (December
2001), pp. 117-1203.
Abstract: "Nations appear to trade too much with themselves and
too little with each other. ... Attempts to explain this `mystery of the
missing trade' have increasingly focused on informal trade barriers,
especially weak enforcement of international contracts... and inadequate
information about international trading opportunities. (This study surveys
research) dealing with the role of networks in overcoming or creating trade
barriers..., the role of intermediaries who can connect foreign agents to
domestic networks, and the ability of transnational production networks to
facilitate technology transfer."
David Schmidt, Robert Shupp, James Walker, T. K. Ahn, and Elinor Ostrom,
"Dilemma Games: Game Parameters and Matching Protocols",
Journal of Economic Behavior and Organization 46 (2001), 357-377.
Abstract: This study examines the impact of changes in
pecuniary payoffs and the linkages between players in the game environment on
strategy choice in repeated Prisoner's Dilemma (PD) games.
John Skvoretz,
"Complexity Theory and Models for Social Networks,"Complexity,
Volume 8, No. 1, September-October 2002, 47-55.
Abstract: "Much work in complexity theory employs
agent-based models in simulations of systems of multiple agents. Agent
interaction follows some standard types of network topologies. My aim is to
assess how recent advances in the statistical modeling of social networks may
contribute to agent-based modeling traditions, specifically, by providing
structural characterizations of a variety of network topologies. I
illustrate the points by reference to a computational model for the evolution
of cooperation among agents embedded in neighborhoods and by reference to
complex, real social networks defined by ties of political support between US
Senators as revealed through ties of cosponsorship of legislation."
John Skvoretz is with the Department of Sociology, Sloan College,
University of South Carolina, Columbia.
Steven H. Strogatz, Sync: The Emerging Science of Spontaneous Order,
Hyperion, 338 pp., March 2003. ISBN: 0-786-86844-9
Abstract (from Publishers Weekly, Copyright 2003 Reed Business
Information, Inc.): "Strogatz is a Cornell mathematician and pioneer
of the science of synchrony, which brings mathematics, physics, and biology
to bear on the mystery of how spontaneous order occurs at every level of the
cosmos, from the nucleus on up. In this eminently accessible and
entertaining book..., Strogatz explores synchrony in chaos systems, at the
quantum level, in small-world networks as exemplified by the parlor game `six
degrees of Kevin Bacon' and in human behavior involving fads, mobs and the
herd mentality of stock traders. The author traces how the isolated and
often accidental discoveries of researchers are beginning to get into the
science of synchrony, and he amply illustrates how the laws of mathematics
underlie the universe's uncanny capacity for spontaneous order."
Steven Strogatz is a Professor of Theoretical and Applied Mechanics
and a member of the Center for Applied Mathematics at Cornell University,
Ithaca, New York.
Steven H. Strogatz, "Exploring Complex Networks"(pdf,589KB),
Nature, Volume 410, No. 6825, March 8, 2001.
Abstract: This article includes a summary of Strogatz's work with Duncan Watts
on "small-world networks" that has started a major new field of research
within network theory. The author also discusses more generally how the study of
networks pervades all of science and everyday life. As examples, he points
to food webs, power transmission lines, the World-Wide Web, and the neural
network of nematode worms. He provides an introduction to terminology and
concepts from nonlinear dynamics used in the study of complex networks.
Troy Tassier and Filippo Menczer,
"Emerging Small-World Referral Networks
in Evolutionary Labor Markets",
IEEE Transactions on Evolutionary Computation, Volume 5, Number 5,
October 2001, 482-492..
Abstract: The authors construct an ACE labor market
model in which potential workers engage in both social network formation and
direct job search. They show that the evolved social networks have "small
world network" properties in the sense that they are both very clustered
(locally structured) and have global reach, and that these two properites
enhance the ability of the social networks to perform as job referral
networks. Nevertheless, as evolution progresses, agents end up expending
more energy on social network formation and/or direct job search than is
socially efficient.
Abstract: "Although many workers find employment through weak ties, previous studies have shown little empirical support for a connection between weak ties and income. In this article, I explain one reason why the survey methods used in previous studies underestimate, perhaps greatly, the effect of weak ties on income. In addition, I demonstrate a more direct method of estimating the effect of weak ties on income by using information from the General Social Survey on the overlap of close friends of respondents. I find that the range of social connections provided by weak ties has a significant and economically meaningful effect on income."
Leigh Tesfatsion, "Structure, Behavior, and Market Power in an
Evolutionary Labor Market with Adaptive Search"(pdf,295KB),
Journal of Economic
Dynamics and Control 25 (2001), pp. 419-457.
The published article is also available from
Science Direct.
Abstract:
This study undertakes a systematic experimental investigation of the relationship between market power and labor market structure (concentration and capacity conditions) when workers and employers preferentially match based on past worksite experiences. For each tested market structure, workers and employers repeatedly seek preferred worksite partners based on continually updated expected utility, engage in efficiency-wage worksite interactions modeled as prisoner's dilemma games, and evolve their worksite behaviors over time. A key finding is the presence of strong learning and network effects. Each tested market structure maps into a "spectral" distribution of observed interaction networks exhibiting one dominant attractor (frequent network pattern) with one or two weaker attractors (less frequent network patterns). Market structure is strongly predictive for the relative market power of workers and employers across all network attractors, but the magnitudes of the market power levels attained by workers and employers vary widely across the network attractors.
Leigh Tesfatsion, "Hysteresis in an Evolutionary Labor Market with
Adaptive Search,"(ps,216KB),
(pdf,534KB),
pp. 189-210 in S.-H. Chen (ed.), Evolutionary
Computation in Economics and Finance, Physica-Verlag Heidelberg, New
York, 2002
Abstract:
This study undertakes a systematic experimental investigation of hysteresis (path dependency) when workers and employers preferentially match based on past worksite experiences. It is shown that two distinct hysteresis effects can arise, network and behavioral, when workers and employers interact strategically and evolve their worksite behaviors over time. These hysteresis effects result in persistent heterogeneity in earnings and employment histories across agents who have no observable structural differences. At a more global level, these hysteresis effects are shown to result in a one-to-many mapping between treatment factors and experimental outcomes. These hysteresis effects may help to explain why excess earnings heterogeneity is commonly observed in real-world labor markets.
Leigh Tesfatsion, "Preferential Partner Selection in Evolutionary
Labor Markets: A Study in Agent-Based Computational Economics"(ps,130KB),
pp. 15-24 in V. W. Porto, N. Saravanan, D. Waagen, and A. E. Eiben (eds.),
Evolutionary Programming VII, Proceedings of the Seventh Annual
Conference on Evolutionary Programming, Springer-Verlag, Berlin, 1998.
Abstract: This ACE study develops a computational labor
market framework for studying the formation and evolution of contractual
networks between workers and employers. Resource-constrained workers and
employers choose and refuse contractual partners on the basis of continually
updated expected utility, engage in risky worksite interactions modelled as
two-person "efficiency-wage" prisoner's dilemma games, and evolve their
work-site strategies over time on the basis of past worksite earnings.
Illustrative computational experiments are reported and interpreted.
Leigh Tesfatsion, "A Trade Network Game with Endogenous Partner
Selection"(pdf,401KB),
(ps,151KB),
pp. 249-269 in H. M. Amman, B. Rustem, and A. B. Whinston
(eds.), Computational Approaches to Economic Problems, Kluwer Academic
Publishers, 1997
Abstract: This ACE study develops a computational
trade network game (TNG) framework for exploring the interplay between
evolutionary game dynamics and preferential partner selection in buyer-seller
markets. The TNG framework consists of successive generations of
resource-constrained traders who choose and refuse trade partners on the
basis of continually updated expected payoffs, engage in risky trades
modelled as two-person games, and evolve their trade strategies over time.
Preliminary computer experiments are reported which suggest that the standard
optimality properties used to judge the desirability of matching mechanisms
in static market contexts may be inadequate measures of optimality from an
evolutionary perspective.
For additional information regarding TNG research articles and
software, see the
TNG Home Page.
Leigh Tesfatsion,
"How Economists Can Get Alife: Abbreviated Version"(html),
a summary version of "How Economists Can Get Alife," pages 533-561 in W.
Brian Arthur, Steven Durlauf, and David Lane, The Economy as an Evolving
Complex System II, Proceedings Volume XXVII, Santa Fe Institute Studies
in the Sciences of Complexity, Addison-Wesley, 1997.
Abstract: This study argues the importance of
considering who is trading with whom, with what regularity, and why, in
economic markets, especially those with small and intermediate numbers of
participants in which price is only one of several strategic considerations.
It discusses how agent-based computational modeling tools adapted from the
newly developing field of artificial life (alife) provide a potentially
promising way to study the formation and evolution of such economic networks.
Stanley Wasserman and Katherine Faust, Social Network Analysis:
Methods and Applications, Cambridge University Press, Cambridge, 1994.
Abstract: "(This book) reviews
and discusses methods for the analysis of social networks with a focus on
applications of these methods to many substantive examples."
Duncan J. Watts and Steven H. Strogatz,
"Collective Dynamics of `Small-World' Networks,"Nature,
Volume 393, No. 6684, 18 June 1998, 440-442.
Duncan J. Watts, Six Degrees: The Science of a Connected Age, W.
W. Norton and Co., 368 pp., February 2003. ISBN: 0-393-04142-5
Abstract: "(Watts is) the
pioneering young scientist whose work on the structure of small worlds has
triggered an avalanche of interest in networks. In this remarkable book,
(he) sets out to explain the innovative research that he and other scientists
are spearheading to create a blueprint of our connected planet. Whether they
bind computers, economies, or terrorist organizations, networks are
everywhere in the real world, yet only recently have scientists attempted to
explain their mysterious workings."
Duncan Watts is with the Department of Sociology at Columbia
University.
Duncan J. Watts, Small Worlds: The Dynamics of Networks Between Order
and Randomness, Princeton University Press, October 1999, 262 pp., ISBN
0-69-100541-9.
Abstract: "How do networks
matter? Simply put, local actions can have global consequences, and the
relationship between local and global dynamics depends critically on the
network's structure. Watts illustrates the subtleties of this relationship
using a variety of simple models --- the spread of infectious disease through
a structured population; the evolution of cooperation in game theory; the
computational capacity of cellular automata; and the synchronisation of
coupled phase-oscillators. ...This fascinating exploration will be fruitful
in a remarkable variety of fields, including physics and mathematics, as well
as sociology, economics, and biology."
Duncan J. Watts is with the Department of Sociology at Columbia
University.
G. Weisbuch, Alan P. Kirman, and Dorothy Herreiner, "Market
Organization,"Economic Journal 110(465), 2000, 411-436.
Douglas R. White (Guest Editor), Special Issue on Networks and
Complexity,
Complexity,
Volume 8, Number 1, September-October 2002.
Abstract: This special issue, guest-edited by Douglas
R. White (Anthropology, UC Irvine), grew out of the August 2002 Founding
Workshop for the Santa Fe Institute's Network Dynamics Program, directed by
James Crutchfield (Program Director, SFI) and Duncan Watts (Sociology,
Columbia University).
H. Peyton Young,
"Social Dynamics: Theory and Applications",
in Leigh Tesfatsion and Kenneth L. Judd (editors),
Handbook of Computational Economics, Vol. 2: Agent-Based Computational
Economics, Handbooks in Economics Series, North-Holland/Elsevier, Amsterdam,
Spring 2006.
Abstract:
Agent-based models typically involve large numbers of
interacting individuals with widely differing characteristics, rules
of behavior, and sources of information. The dynamics of such
systems can be extremely complex due to their high dimensionality.
This chapter discusses a general method for rigorously analyzing the
long-run behavior of such systems using the theory of large
deviations in Markov chains. The theory highlights certain
qualitative features that distinguish agent-based models from more
conventional types of equilibrium analysis. Among these
distinguishing features are: local conformity versus global
diversity, punctuated equilibrium, and the persistence of particular
states in the presence of random shocks. These ideas are illustrated
through a variety of examples, including competition between
technologies, models of sorting and segregation, and the evolution
of contractual customs.
The Trade Network Game: Demonstration Software (Network Formation) (html)
David McFadzean, Deron Stewart, and Leigh Tesfatsion, "A Computational
Laboratory for Evolutionary Trade Networks"(pdf,508KB),
IEEE Transactions on
Evolutionary Computation, Vol. 5, No. 5, October 2001, pp. 546-560.
The published article is also available at
IEEE Xplore.
Abstract: This report presents, motivates, and
illustrates the use of a computational laboratory for the investigation of
evolutionary trade network formation among strategically interacting buyers,
sellers, and dealers. This Trade Network Game Laboratory (TNG Lab) is
targeted for the Microsoft Windows desktop. The TNG Lab is both modular and
extensible and has a clear, easily operated graphical user interface. It
permits visualization of the formation and evolution of trade networks by
means of run-time animations. Data tables and charts reporting descriptive
performance statistics are also provided in real time. The capabilities of
the TNG Lab are demonstrated by means of labor market experiments.
For an automatic installation program for the TNG Lab, along with
TNG Lab tutorials and other supporting materials, visit the
TNG Home Page.
Annotated list of pointers to
ACE/CAS Computational Laboratories and Demonstration Software.
Included are many demos of possible interest for the agent-based
computational modeling of networks (e.g., demos for several distinct versions
of the Schelling Segregation Model, a Trade Network Game demo, demos of
cellular automata, and demos of flocking behavior).
Annotated list of pointers to
ACE/CAS General Software and Toolkits.
Included at this site are social network analysis packages such as ORA and
toolkits such as
Repast
that support agent-based network modeling.
Resource Sites, Groups, and Some Early Individual Researchers
Formation of Economic and Social Networks
(Tesfatsion, Iowa State University). Resources at this site include an
annotated list of pointers to research groups and individual researchers
studying economic and social network formation.
Internet Site for the Economics of Networks
(Economides, New York University). This site provides a collection of
information on economic issues related to networks, such as the telephone and
fax communications networks, the Internet, financial exchange and credit card
networks, and "virtual networks" such as the virtual network of all Windows
or all Mac computers.
Kathleen M. Carley
(School of Computer Science, Carnegie Mellon University, Pittsburgh, PA): Computational and
social and organization theory; dynamic social networks; multi-agent network models; group,
organizational, and social adaptation and evolution; statistical models for dynamic network
analysis and evolution; computational text analysis; and the impact of telecommunication
technologies on communication and information diffusion within and among groups.
Robin Cowan
(Maastricht Economic Research Institute on Innovation and Technology (MERIT),
University of Maastricht, the Netherlands, and Economics Department,
University of Waterloo, Canada): Dynamics of networks and network
structures; Economics of technology adoption; Economics of knowledge
generation; Technological competition and standardization; Consumption
dynamics; Methodology.
John Duffy
(Department of Economics, University of Pittsburgh, Pennsylvania):
Incorporation of learning in computational economic models; Using genetic
algorithms to model how agents learn and adaptively update their forecasts;
Endogenous network formation.
Giorgio Fagiolo
(Sant'Anna School of Advanced Studies, Pisa, Italy): Endogenous networks;
Local interaction models; Endogenous neighborhood formation; Segregation in networks; Minority games.
Matthew O. Jackson
(Economics, Stanford University, CA): Strategic models of social and economic
networks; Evolution of social and economic networks; Coalition and Party
Formation in legislative voting games; Reputation versus social learning.
Michael W. Macy
(Sociology, Cornell University, Ithaca, N.Y.): Informal social control in
on-line trading communities; Coalition formation in exchange networks;
Trust and cooperation in the U.S. and Japan; Management fads; Collective
action; Evolutionary game theory; Deviance and social control; Social
psychology; Social Exchange theory; Rational choice.
Filippo Menczer
(Center for Complex Networks and Systems Research, Indiana University,
Bloomington): Labor market referral networks as "small-world" networks;
Adaptive and evolutionary computation applied to intelligent and distributed
information agents; Interactions between learning and evolution; Distributed
decision making; Artificial life.
Anna Nagurney
(Finance and Operations Management Department, University of Massachusetts,
Amherst, Massachusetts): Network models of large-scale financial,
transportation, and regional economic systems; Algorithms on serial and
parallel computer architectures to predict flows of funds, people, goods, and
services.
Michael Neugart
(Technical University Darmstadt, Germany): Labor economics;
Endogenous matching functions; Nonlinear economic dynamics; Political
economics; Agent-based computational modeling; Applied econometrics.
Denis Phan
(CNRS & Université Paris IV Sorbonne, France):
Global and local effects of interaction structures; Network externalities;
Small-world networks, phase transitions, and avalanches in ACE frameworks;
Moduleco (an agent-based computational laboratory); Cognitive economics;
Generic properties of complex adaptive systems.
Leigh Tesfatsion
(Economics, Iowa State University, Ames, Iowa): Trade network games;
Formation and evolution of networks in labor markets; Transmission-grid
constrained exchange in electricity markets.
Nick Vriend
(Economics, Queen Mary and Westfield College, University of London):
Dynamics of interactive market processes; Emergent properties of evolving
market structures and outcomes; Learning algorithms; History of economic
thought.
Allen Wilhite
(Economics, University of Alabama in Huntsville):Small-world trading
networks; Decision making when agents are influenced by the decisions of
others.