Meeting the Challenge of Social Problems via Agent-Based Simulation: Post-Proceedings of the Second International Workshop on Agent-Based Approaches in Economic and Social Complex Systems

197 Pages·2003·8.97 MB·English

by  Robert L. Axtell (auth.)

Springer Japan KK
T. Terano, H. Deguchi,
K. Takadama
(Eds.)
Meeting the Challenge of
Social Problems via
Agent-Based Simulation
Post-Proceedings of the Second International
Workshop on Agent-Based Approaches in
Economic and Social Complex Systems
With 76 Figures
, Springer
Takao Terano, Ph.D.
Professor
Graduate School of Systems Management
University of Tsukuba
3-29-1 Ohtsuka, Bunkyo-ku, Tokyo 112-0012, Japan
Hiroshi Deguchi, Ph.D.
Professor
Interdisciplinary Graduate School of Science and Engineering
Tokyo Institute of Technology
4259 Nagatsuta-cho, Midori-ku, Yokohama 226-8502, Japan
Keiki Takadama, Ph.D.
Lecturer
Interdisciplinary Graduate School of Science and Engineering
Tokyo Institute of Technology
4259 Nagatsuta-cho, Midori-ku, Yokohama 226-8502, Japan
ISBN 978-4-431-67982-0 ISBN 978-4-431-67863-2 (eBook)
DOl 10.1007/978-4-431-67863-2
Library of Congress Cataloging-in-Publication Data applied for.
Printed on acid-free paper
© Springer Japan 2003
Originally published by Springer-Verlag Tokyo Berlin Heidelberg New York in 2003
Softcover reprint of the hardcover 1s t edition 2003
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Preface
Social sciencesare moving to thenext stage.One ofthe promisingmethodologies
isagent-basedcomputersimulation.In aseries ofworkshopsonAgent-BasedAp
proaches in Economic and Social Complex Systems (AESCS), ground-breaking
studiesofcomplexeconomicandsocialphenomenausingcomputational approaches
arebeing presentedand discussed. This volume contains papers selectedfrom pre
sentationsattheAESCS '02 held atthe UniversityofTokyo,Japan, onAugust 16,
2002.Theworkshop wasthesecond inaseriesofPacific Rimactivities ininterdis
ciplinary areas ofsocial and computational sciences, the first workshop having
been held inShimane, Japan,May 21-22, 2001.
The objective ofAESCS workshops istopromote worldwide multidisciplinary
activities in multiagent computational economics, organizational science, social
dynamics, andcomplex systems.AESCS brings together researchersandpractitio
nersfromdiverse fields, such ascomputerscience, economics,physics, sociology,
psychology,and complex theory, inorder to understand emergent and collective
phenomenaineconomic,organizational, andsocial systems.AESCS alsoprovides
anopportunityfordiscussion oftheeffectivenessand limitationsofcomputational
models and methodologies forthe social sciences.
ThesecondAESCS workshop focusedontheimportance ofcumulativeprogress
in agent-based simulation in the social sciences through discussions ofcommon
tasks, standardcomputationalmodels,replicationand validationissues,and evalu
ation and verification criteriafor the results.
As mentioned earlier, the chapters ofthis book originated as papers selected
from among those that were presentedatAESCS '02.From the 20 papers submit
ted from five countries, nine regular papers were selected (an acceptance rate of
45%).All papers were reviewed by at least two peer-reviewers, and reviewers'
comments were carefullyconsideredbythe programcommitteemembers for fair
ness and consistency in the selection process.Toensure that current topics are
included, the volume also containsthree invited papers bydistinguishedspeakers.
AESCS '02receivedpartial financial support from(1)aGrant-in-AidforScien
tific Research ofMETI,Japan (B 14380154):Poly-AgentApproachto Social Sys
temModeling and(2)aGrant-in-AidforaResearch Projecton Digital Economy in
the Global Contextand Institutional Design ofaKnowledge-Intensive Society.
v
VI Preface
Wealsoacknowledge thesupportandencouragementofmanypeoplewhohelped
ustohold the workshopand preparethisvolume,withspecialthanks to Professor
Sudo and membersofhis laboratories;to Ms.Goto from theUniversityofTokyo;
and toMs.NakamurafromtheTokyo InstituteofTechnology.Inaddition,wethank
thestaffofSpringer-Verlag,Tokyo,fortheirassistance inpublishing thisvolume.
Wehope that those who are interestedinrecent progressinagent-basedsimulation
inthe socialscienceswill find the book attractive and useful.
TAKAO TERANO GeneralChair
HIROSHIDEGUCHI Organizing Chair
KEIKITAKADAMA Organizing Chair
Conference Committee
General Chair
TakaoTerano, University ofTsukuba, Japan
Organizing Chair
HiroshiDeguchi,Tokyo InstituteofTechnology,Japan
Keiki Takadama,Tokyo Institute ofTechnology & ATR Human Information
Science Laboratories,Japan
Program Committee (in alphabetical order)
Shu-HengChen,NationalChengchi University,Taiwan
Sung-BaeCho,YonseiUniversity,Korea
Peter Dittrich,University ofDortmund,Germany
YoshiFujiwara,ATRHuman Information Science Laboratories,Japan
ToshiyaKaihara,Kobe University, Japan
Hajime Kita,Kyoto University & National Institution for Academic Degrees,
Japan
Koichi Kurumatani, National Institute ofAdvanced Industrial Science and
Technology,Japan
Thomas Lux,Kiel University,Germany
Hideyuki Mizuta,IBMTokyo Research Laboratory, Japan
Yoshiteru Nakamori,JapanAdvanced InstituteofScienceandTechnology, Japan
AkiraNamatame,National DefenseAcademy,Japan
Wataru Souma,ATRHuman Information Science Laboratories,Japan
Keiji Suzuki,Future University-Hakodate, Japan
ShingoTakahashi,Waseda University,Japan
David W.K.Yeung, Hong Kong Baptist University & St. Petersburg State
University,China
MakotoYokoo,NTT CommunicationScience Laboratories,Japan
Contents
Preface V
ConferenceCommittee VII
Part I: Economic Systems
Economics as DistributedComputation
R.L.Axtell 3
Dynamic ResourceAllocationofInvestment and Competitive Growth:R&D
InvestmentandCapital Investment
H.LeeandH.Deguchi 25
Wealth Distributionon Scale-FreeNetworks
w: Souma, Y Fujiwara, and H.Aoyama 37
Part II: Marketing and Management
U-Mart:An Artificial MarketTestbedfor Economicsand MultiagentSystems
T. Terano, Y Shiozawa,H. Deguchi,H. Kita,H. Matsui,H. Sato,I.Ono,
and Y Nakajima 53
The Statistical Properties ofPrice Fluctuation by ComputerAgent in U-Mart
Virtual Futures MarketSimulator
H. Sato,S.Kawachi,andA. Namatame 67
Study onaDynamicResourceAllocationforaCommunicationNetworkBased
on a Market-basedModel
M Ishinishi, H. Deguchi,and H. Kita 77
Human-AgentParticipation in a Business Simulator
M Kobayashi and T. Terano 91
ARole ofMicro-macroLoop forKnowledgeCreationbyHeterogeneousAgents
K.Sato andA.Namatame 107
X Contents
How to ShareKnowledge Effectively?
A.Inuzuka 123
Part III: Social Systems and Methodology
Agent-BasedComputationalMacro-economics:ASurvey
5.-H. Chen 141
The X-MAS SYSTEM: Toward SimulationSystems forCross-modeI-validation
inMultiagent-BasedSimulations
Y.I.L.Suematsu,K.Takadama,N.£. Nawa,K.Shimohara,andO.Katai ....171
AStudyonPedestrian FlowbyUsing anAgentModel- ASimulation Analysis
on the Asagiri OverpassAccident, 2001 -
T. Kaneda,H. Yano, T. Misaka, T. Suzuki.andT. Yamada 185
Author Index 197
Keyword Index 199
Part I: Economic Systems
Economics as Distributed Computation*
RobertL. Axtell
CenteronSocialandEconomicDynamics,TheBrookingsInstitution, 1775Massachusetts
Avenue,NWWashington,DC 20036,[email protected]
Summary. In human societies diverse people act purposively with powerful but
limited cognitive processes, interacting directly with one another through
technologically-facilitated and physically-mediated social networks. Agent-based
computational modeling takes these features of humanity-behavioral
heterogeneity, bounded rationality, network interactions-at face value, using
modern object-oriented programming techniques to create agent populations that
have a high degree ofverisimilitude with actual populations. This contrasts with
mathematical social science, where fantastic assumptions render models so
cartoon-like as to beg credibility-stipulations like identical agents (or a single
'representative' agent), omniscient agents (who accurately speculate about other
agents), Nash equilibrium (macro-equilibrium arising from agent-level
equilibrium) and even the denial ofdirect agent-agent interaction (as in general
equilibrium theory, where individuals interact only with a metaphorical
auctioneer). There is a close connection between agent computing in the positive
social sciences and distributed computation in computer science, in which
individual processors have heterogeneous information that they compute with and
then communicate to other processors. Successful distributed computation yields
coherent computation across processors. When such distributed computations are
executed by distinct software objects instead of physical processors we have
distributed artificial intelligence. When the actions of each object can be
interpreted as in its 'selfinterest' we then have multi-agent systems, an emerging
sub-field ofcomputerscience. Viewing human society as a large-scale distributed
system for the production of individual welfare leads naturally to agent
computing. Indeed, it isargued that agents are the only way for social scientists to
effectivelyharnessexponentialgrowth incomputational capabilities.
Keywords. economics,distributedcomputation,multi-agentsystems
• Preliminaryversions of this paper were presented at the U.S. National Academyof
Sciencescolloquium"AdaptiveAgents,IntelligenceandEmergentHumanOrganization:
CapturingComplexity throughAgent-BasedModeling"held at the Arnoldand Mabel
BackmanCenterinIrvine,California(October2001),theThirdTrentoSummerSchool
on Adaptive Economics, held at the Computable and Experimental Economics
Laboratory at the University of Trento, Italy (July 2002), and at the Agent-Based
Approaches toEconomicandSocialComplexSystems(AESCS),Tokyo,Japan(August
2002).
T. Terano et al. (eds.), Meeting the Challenge of Social Problems via Agent-Based Simulation
© Springer-Verlag Tokyo 2003