Simulating Society: A Mathematica® Toolkit for Modeling Socioeconomic Behavior

218 Pages·1998·10.33 MB·English

by  Richard J. Gaylord

Simulating Society
Richard J. Gaylord Louis J. D'Andria
Simulating Society
A Mathematicct Toolkit for Modeling
Socioeconomic Behavior
IlIffiiiis· .
~
Springer
Richard J. Gaylord
Department of Materials Science and Engineering
University of Illinois at Urbana-Champaign
Urbana, IL 61801
USA
LouisJ. D'Andria
Wolfram Research, Inc.
100 Trade Center Drive
Champaign, IL 61820-7237
USA
Library of Congress Cataloging-in-Publication Data
Gaylord, Richard J.
Simulating society : a Mathematica toolkit for modeling
socioeconomic behavior / Richard 1. Gaylord, Louis J. D' Andria.
p. cm.
Includes bibliographical references and index.
1. Social interaction-Computer simulation. 2. Socialization
-Computer simulation. 3. Mathematica (Computer file) 1. D' Andria,
Louis 1. II. Title.
HM291.G375 1998
302'.0285--dc21 98-17543
Printed on acid-free paper.
© 1998 Springer Science+Business Media New York
Originally published by Springer-Verlag New York, Inc. in 1998
Ali rights reserved. This work may not be translated or copied in whole Of in pari without the writlen
permission of the publisher Springer-Science+Business Media, LLC, except for brief excerpts in
connection with reviews or scholarly ana1ysis. Use in connection with any form of information storage
and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now
known or hereafter developed is forbidden. The use of general descriptive names, !rade names,
trademarks, etc., in this publication, even if the former are not especia1ly identified, is not to be taken as
a sign that such names, as understood by the Trade Marks and Merchandise Marks Act, may according1y
be used freely by anyone.
Mathematica is a registered trademark ofWolfram Research, Inc.
Production managed by Steven Pisano; manufacturing supervised by Jacqui Ashri.
Photocomposed pages prepared from the authors' Mathematica notebook files.
987654321
ISBN 978-0-387-98532-9 ISBN 978-1-4612-1726-8 (eBook) SPIN 10659681
DOI 10.1007/978-1-4612-1726-8
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Tomylifecompanion.Carole. Theonething Icouldneverthrowaway ismy feeling
foryou. Andtoakindredspirit,CalvinofCalvinandHobbes.
-R.J.G.
ToSuzanne. forthe inspiration, support,and loveshecheerfully and incessantly gave
duringandinspiteofthecreationofthisbook.
-L.1.D.
Although agent-based modeling employs simulation, it does not aim to provide an
accurate representation of a particular empirical application. Instead, the goal of
agent-based modeling is to enrich our understanding of fundamental processes that
may appearinavariety ofapplications. Thisrequires adhering tothe KISS principle,
whichstandsforthearmyslogan"keepitsimple, stupid."
-RobertAxelrod
Foreword
Richard Gaylord and Lou D'Andria's book is not a standard introduction to
computational social sciences filled with long passages on the history ofeconomic
thought. Instead,thisisabookdescribing how tocreatecomputermodelsofcomplex
human interactions. These modelsstandinsharpcontrasttothe static, "supplyequals
demand" models of introductory economics, though that is not to say that standard
economic models are not informative, just that they are predictable. In contrast, the
modelspresentedinthisbookcanexhibitperpetuallynovelbehavior.
A computational model relies on individual agents (people) who have preferences
andcantakeactions. Agentscan walk. They can move tonew neighborhoods ifthey
feel uncomfortable in theirpresentsituation.They can play games with theirfriends,
or choose to hang with a new crowd. They can share gossip. They can chat on the
phone. While these agents are reasonably smart, they do not always optimize. To
borrow HerbSimon's words, they areboundedly rational. Theygoabout life muchin
the same way that we do. They rely on heuristics-rules ofthumb-in their day to
day interactions. These rules are not setin stone. In fact, ifan agentfinds that she is
usingastupidrule,shemayabandonitinfavorofsomethingbetter.
In watching and analyzing the microlevel and aggregate behavior ofthese artificial
agents, we can learn much about ourown world. We learn that gossip has its good
side and thatthe presenceofracial segregation need not imply that individual agents
areracist.
This latter finding is due to Thomas Schelling. whose book Micromotives and
Macrobehavior still informs those of us interested in dynamic models. Gaylord and
D'Andria performamuch needed serviceby making thismodel available toall. They
xii Foreword
also extend Schelling's model by allowing agents to relocate based on endogenous
(acquired)characteristics. Forexample, Imay choosetomove toanotherhouseifmy
neighbor decides to form a rock band, or I may choose to move out of town if my
fellowcitizensvotetocutpublicservicesorraisetaxestoalevelIfindobjectionable.
The Gaylord and D'Andria book carves out an important niche in this growing field
ofcomplexity, owing to its accessibility. Although many models ofartificial society
make their computer codes available publicly, these often consist of thousands of
lines ofinelegant code. By relying bothon Mathematica, a high-level language, and
on exacting standards, the authors construct elaborate models with minimal, often
beautiful, code. For example, some of their models require less than fifty lines of
code. Gaylord and D'Andriaalsodeconstruct theircode and discuss how to extend it
to accommodate richer models. Finally, their code produces readable, analyzable
output. They reveal that with a few simple subroutines, some courage, moderate
intelligence, andalittleheart,anyonecancreateartificialsocieties.
This book contains models that are both bottom-up and complex: the accumulated
behaviors of autonomous agents generate outcomes, and agents respond to an
environment that they in tum define by their actions. The more advanced models in
the book include adaptive behavior: agents abandon unsuccessful behavioral rules.
Herein lies thedifference between social sciencemodels and those from the physical
sciences-people can change. We can copy strategies of others, alter our own
actions, or act out of caprice. Carbon atoms never consciously decide to throw
caution to the wind and act like helium atoms. Yet poor people sometimes act rich,
smart people sometimes act foolish, and conservative people sometimes take huge
risks. Although this book only dips its toe into the water on the issue of how to
construct artificial adaptive agents, it does provide a sufficient introduction to get
peoplestarted.
The topics addressed in this book-movements, fads, norms, game playing, social
networks, culture, and conformity-span traditional social scientific boundaries.
Many ofthe models take as a fundamental assumption that others-friends, family,
and peers-influence our actions. Recently, several economists, notably Steven
Durlauf of the Santa Fe Institute and the University of Wisconsin, have begun to
analyze the role ofsocial influence in explaining persistent social problems such as
crime, drug use, out-of-wedlock births, and school attendance. These problems are
difficult to analyzeempirically, so simulations and other forms oftheorizing seem a
logicalfirststepinorganizingourcollectivethinking.
This book was not written with the intent ofinfluencing social policy directly and,
given itsintent, it wisely avoids long discussions on patterns ofdrug use, crime, and
other "heavy" topics. Instead, itprovidesan introduction. Itsays, "Hereis how todo
make your own models." The task of interpretation is left to the readers. We can
attach weight to the insights we gather-asking, for example, whether these models
sayanythingaboutwhycrackbecamesopopularsofast-orwecanjusthavefun.
Foreword xiii
In sum.this bookmeritsacareful read. Forthe noneconomist. this bookshould whet
yourappetitefor adeeperlookatsocial science models. Forsocial scientists who use
Mathematica for the sole purpose ofsolving algebraic problems, here's a chance to
seeitsawesomepower.
Gaylord and D'Andria have included many exercises and extensions. some ofwhich
are open research questions. I encourage readers to go beyond these and formulate
their own models, to think more broadly. Explore. Take risks. Construct models of
product competition. movie demand. marriage markets. political preferences,
religious affiliation, tax evading. investment strategies. traffic jams. orjoke telling.
Given the many moviequotes containedthroughout the text, Iclose by paraphrasing
a certain Mr. Gump. This book is "like a box of chocolates." You really never do
know what you mightget. That's the wonderofcomputational modeling. You define.
theworld.thensitbackandwatchitevolve.
ScottE. Page
DepartmentofEconomics
UniversityofIowa