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Preface
Agent-based Computational Methods applied to the fields of Economics, Manage-
ment Sciences, Game Theory or Finance^ have received a great deal of academic
interest these past years, in relation with the Complex System approaches. Those
fields deal with the computational study of economies (at large), as complex adap-
tive systems, implying interacting agents with cognitive skills. One of the first use
of agent based models has been popularized by Axelrod, [1], in his theory of evo-
lution of cooperation. In this early work, he used extensively computational simu-
lations and methods in order to study strategic behaviour in the Iterated Prisoner's
Dilemma. This work is still influencing many researches in various scientific fields.
It has for instance been the foundations of a new approach of Game Theory, based
on computational ideas.
In the mid eighties, under the impulsion of the Santa-Fe Institute, and especially
Christopher Langton, [3], a new field of research, called Artificial Life (AL), has
emerged. The idea of AL was to mimic real life under its various aspects to under-
stand the basic principles of life. This has lead to encompass wider ideas such as com-
plexity, evolution, auto-organisation and emergence. All concepts induced by these
approaches have influenced social scientists among others. Following these initial
attempts to mix computational approaches and social sciences, for instance among
the pioneering works using Agent-based Computational Economics in finance, one
can refer to the Artificial Stock Market, [4]. This model, based on bounded rational-
ity and inductive reasoning, [5], is one of the first allowing correct simulations of
real world stock market dynamics. This work has been done by people coming fi-om
various scientific fields (Economics, Game Theory, Computer Science and Finance).
All these approaches intensively use computer simulation as well as artificial in-
telligence concepts mostly based on multi-agents systems. In this context, some of
the most used models come from Game Theory. Therefore, Agent-based Compu-
tational Simulations is more and more an important methodology in many Social-
Sciences. It becomes now widely used to test theoretical models or to investigate
their properties when analytical solutions are not possible.
Le. ACE, ABMS, COT, ACF
VI Preface
Artificial Economics'2005 is one attempt to gather scientists from various hori-
zons that directly contribute to these fields. The book you have in hands reproduces
all the papers that have been selected by the programme committee. AE'2005 aims
and scopes were to present computer-science based multi-agent methodologies and
tools with their applications to social-scientists (mainly people fi'om economics and
the management sciences,) as well as to present uses and needs of multi-agent based
models and their constraints, as used by these social scientists, to computer scien-
tists. Additionally, it has been a great occasion to favor the meeting of people and
ideas of these two communities, in order to be able to construct a much structured
multi-disciplinary approach.
For its first edition. Artificial Economics has presentend recent scientific ad-
vances in the fields of ACE, ABMS, CGT, ACF, but has also been widely open to
methodological surveys. Two prestigious invited-speakers have proposed analysis
and surveys on major issues related to Artificial Economics topics.
Cristiano Castelfranchi, from the Institute of Cognitive Sciences and Technolo-
gies, University of Siena, has developed a talk on "The Invisible (Left) Hand" . For
Pr. Catsellfanchi, Agent-based Social Simulation will be crucial for the solution of
one of the most hard problems of economic theory : the spontaneous organization of
a dynamic social order that cannot be planned but emerges out of intentional plan-
ning agents guided by their own choices. This is the problem that Hayek assumes
to be the real reason for the existence of the Social Sciences. In his talk, Pr Castell-
franchi has examined the crucial relationships between the intentional nature of the
agents * actions and their explicit goals and preferences, and the possibly unintended
finality or function of their behavior [He] argues in favor of cognitive architectures
in computer simulations and proposes some solutions about the theoretical and func-
tional relationships between agents' intentions and non-intentional purposes of their
actions.
[For him,] social order is not necessarily a real order or something good and desir-
able for the involved agents; nor necessarily the best possible solution. It can be bad
for the social actors against their intentions and welfare although emerging from
their choices and being stable and self-maintaining. Hayek's theory of spontaneous
social order andElster's opposition between intentional explanation and functional
[are also] criticized.
Robert Axtell, from The Brookings Institution, Washington DC and the Santa Fe
Institute, has emphasized a very stimulating reflection on "Very Large-Scale Multi-
Agent Systems and Emergent Macroeconomics". For Dr. Axtell, the relatively few
applications of agent-based computing to macroeconomics retain much of the rep-
resentative agent character of conventional macro. [Robert Axtell] points out that
hardware developments will soon make possible the construction of very large scale
(one million to 100 million agent) models that obviate the need for representative
agents -either representative consumers, investors or single-agent firms.
[He also argues] that the main impediment to creating empirically-relevant artificial
agent economies on this scale is our current lack of understanding of realistic behav-
ior of agents and institutions. [He] claims that this software bottleneck-what rules to
write for our agents ?-is the primary challenge facing our research community.
Preface VI
Artificial Economics 2005 has been a two-days symposium. 20 papers have been
selected among roughly 40 submitted extended abstracts. The reviewing process has
been blind, and each paper has been reviewed by three referees. Space and time lim-
itations are the reasons why no more papers have been accepted, although many of
the rejected submissions were really interesting. Nevertheless, the choice of avoid-
ing parallel sessions has been made to favor interactions between participants. The
contributions have been gathered in six sessions, each of them devoted to one of
the following topics: Artificial Stock Markets, Learning in models, Case-Studies and
Applications, Bottom-Up approaches. Methodological issues and Market Dynamics.
This book is organized according to the same logic.
Artificial Economics'2005 as well as this book is the result of the combinatory
efforts of:
Frederic AMBLARD - Universite de Toulouse 1, France
Gerard BALLOT - ERMES, Universite de Paris 2, France
Bruno BEAUFILS - LIFE, USTL, France
Paul BOURGINE - CREA, Ecole Polytechnique, France
Olivier BRANDOUY - CLAREE, USTL, France
Charlotte BRUUN - Aalborg University, Danemark
Jose Maria CASTRO CALDAS - ISCTE, DINAMIA, Portugal
Christophe DEISSENBERG - GREQAM, France
Jean-Paul DELAHAYE - LIFE, USTL, France
Jacques FERBER - LIRMM, Universite de Montpellier II, France
Bernard FORGUES - CLAREE, USTL, France
Wander JAGER - University of Groningen, The Netherlands
Marco JANSSEN - CIPEC, Indiana University, USA
Alan KIRMAN - GREQAM, France
Philippe LAMARRE - LINA, Universite de Nantes, France
Luigi MARENGO - DSGSS, Universita di Teramo, Italy
Philippe MATHIEU - LIFE, USTL, France
Denis PHAN - Universite de Rennes I, France
Juliette ROUCHIER - GREQAM, France
Elpida TZAFESTAS - National Technical University of Athens, Greece
Nicolaas VRIEND - Queen Mary University of London, United Kingdom
Bernard WALLISER - CERAS, ENPC, France
Murat YILDIZOGLU - IFREDE-E3I, Universite Montesquieu Bordeaux IV, France
We also want to thank Rene Mandiau from the Universite of Valenciennes, as
he has been a very precious additional referee. Let all of them be thanked for their
participation in this scientific event, that surely appeals for fixrther similar manifes-
tations.
Villeneuve d'ascq, Philippe Mathieu
June 2005 Bruno Beaufils
Olivier Brandouy
VI Preface
References
1. R. Axelrod and W.D. Hamilton (1981), The evolution of cooperation. Science, pp. 1390-
1396
2. R. Axelrod (1984), The evolution of cooperation, Basic Books
3. C. Langton (1995), Artificial Life, an overview. The MIT Press
4. R.G. Palmer and W.B.Arthur and J.H. Holland and B. LeBaron and R Tayler (1994),
Artificial Economic Life : A Simple Model of a Stockmarket, Physica D, vol 75, pp. 264-
274
5. B. Arthur (1994), Inductive Reasoning and Bounded Rationality: the El-Farol Problem,
American Economic Review, vol 84, pp. 406-417
Contents
Artificial Stock Markets
Time Series Properties from an Artificial Stock Market with a Walrasian
Auctioneer
Thomas Stumpert, Detlef Sese, Make Sunderkoter 3
Market Dynamics and Agents Behaviors: a Computational Approach
Julien Derveuw 15
Traders Imprint Themselves by Adaptively Updating their Own Avatar
Giles Daniel, Lev Muchnik, Sorin Solomon 27
Learning in Models
Learning in Continuous Double Auction Market
Marta Posada, Cesdreo Hernandez, Adolfo Lopez-Paredes 41
Firms Adaptation in Dynamic Economic Systems
Lilia Rejeb, Zahia Guesoum 53
Firm Size Dynamics in a Cournot Computational Model
Francesco Saraceno, Jason Bar 65
Case-Studies and Applications
Emergence of a Self-Organized Dynamic Fishery Sector: Application to
Simulation of the Small-Scale Fresh Fish Supply Chain in Senegal
Jean Le Fur 79
Multi-Agent Model of Trust in a Human Game
Catholijn M. Jonker, Sebastian Meijer, Dmytro Tykhonov, Tim Verwart 91
