PS 793, Fall 2003
Professor Robert Axelrod
Office Hours: Tuesdays 2-4 at 409 Lorch
Complexity theory is a new
interdisciplinary approach to understanding dynamic processes involving the
interaction of many actors. A primary
methodology of complexity theory is agent-based modeling. Agent-based modeling involves specifying how
individual agents (such as people, nations, or organizations) interact with
each other and with their environment.
Computer simulation is then used to discover the emergent properties of
the model, and thereby gain insights into dynamic processes that would be too
difficult to model with standard mathematical techniques.
Agent-based modeling provides a
third way of doing science in addition to the traditional methods of deduction
and induction. Like deductive models,
an agent-based model starts with a well-defined set of assumptions. But unlike deductive models, an agent-based
framework is capable of revealing consequences through simulation that cannot
be deduced with standard mathematical techniques. And like induction, the main method of finding these consequences
(and perhaps new insights) is through analysis of a set of data - in this case
data generated by running the computer simulation. The goal is to discover new
principles about the dynamics of complex systems, especially complex adaptive
systems that are typical of social processes.
There is no need to assume rationality.
The course will consider a wide
variety of applications of agent-based models to the social sciences, including
residential segregation, revolution, social influence, urban growth, war,
alliances, organizational change, elections, and stock markets. Among the issues to be examined across
models are: path dependence, sensitivity to initial conditions, emergence of
self-organized structure, adaptation to a changing environment, co-evolution,
information cascades, and criteria for judging the value of an agent-based
model.
The grade will be based on four
exercises (6% each; due September 18 to October 9), the research design for the
project (10%; due October 30), and the project report (64%; due noon December
15).
This syllabus is on the web with
live links. See “Recent Courses” in Axelrod’s personal home page.
http://www-personal.umich.edu/~axe/
Information and resources for the
exercises are at:
http://pscs.physics.lsa.umich.edu/Software/CC/CCAB.html
Knowledge of a programming language
(such as BASIC, Pascal, C, C++ or Java) is required. Some basic statistics will be helpful, but is not required.
The course is intended for graduate
students in a wide variety of fields, not just political science.
Office hours are Tuesdays 2-4 at 409
Lorch Hall. The phone number is 763-0099. I can also be reached on e-mail at axe@umich.edu.
My personal web page is http://www-personal.umich.edu/~axe/
A
course pack has been prepared by Dollar Bill Copy but is available for sale
only at Ulrich’s Bookstore, 549 E. University, 662-3201.
1.
Introduction to Complexity Theory. September 4.
Krugman,
Paul, 1996. The Self-Organizing Economy, Malden, MA: Blackwell, pp.
16-21. On Schelling’s residential segregation model.
Rauch, Jonathan, “Seeing Around
Corners,” Atlantic, April 2001. http://www.theatlantic.com/issues/2002/04/rauch.htm (Skip section on “Mr. Schelling’s
Neighborhood”).
Center for the Study of Complex
Systems, “What is the Study of Complex Systems,” and “Examples” from http://www.pscs.umich.edu/complexity.html
Vicsek, Tamas, “Complexity: The Bigger
Picture,” Nature 418, 131 (2002).
http://www.nature.com/cgi-taf/DynaPage.taf?
2.
Agent-Based Modeling. September 11.
Resnick,
Mitchel 1994. Turtles, Termites, and Traffic Jams: Explorations in Massively
Parallel Microworlds, Cambridge, MA: MIT Press, p 3-19 on decentralization.
Axelrod,
Robert and Ross A. Hammond, 2003. “The
Evolution of Ethnocentric Behavior,” Revised version of a paper prepared for
delivery at the Midwest Political Science Association, April 3-6, 2003.
Chicago, IL. Available at
http://www-personal.umich.edu/~axe/research/AxHamm_Ethno.pdf
Animation at http://www-personal.umich.edu/~axe/Movie%20Midwest%20Doc.htm
Axelrod,
Robert, 1997. "Advancing the Art of Simulation in the Social
Sciences" in Rosario Conte, Rainer Hegselmann and Pietro Terna (eds.), Simulating
Social Phenomena. Berlin: Springer.
3.
Organizations. September 18.
Exercise
1 due.
March,
James G. 1991. "Exploration and Exploitation in Organizational
Learning," Organization Science,
2, pp. 71-87.
Simon,
Herbert, 1982. The Sciences of the
Artificial second edition, Cambridge, MA: MIT Press, pp. 193-230.
Epstein,
Joshua, 2003. “Growing
Adaptive Organizations: An Agent-Based Computational Approach,” Santa Fe
Institute Working Paper. http://www.santafe.edu/sfi/publications/Working-Papers/03-05-029.pdf
(Note: the figures are best viewed in
color.)
4.
Social Influence. September 25.
Exercise
2 due.
Kennedy,
James, 1998. “Thinking Is Social: Experiments with the Adaptive Culture Model,”
Journal of Conflict Resolution, 42, pp. 56-76. Available through
Proquest at http://proquest.umi.com/pqdweb
Axtell,
Robert and Joshua Epstein,1999.
“Coordination in Transient Social Networks: An Agent-Based Computational
Model of the Timing of Retirement,” Brookings CSED Working Paper No. 1, May
1999. Online at http://www.brook.edu/es/dynamics/papers/retirement/retirement.htm
The
Java model is available for running at http://www.brook.edu/es/dynamics/models/retirement/
5.
Genetic Algorithm and the Prisoner's Dilemma. October 2.
Exercise
3 due.
Holland,
John H. 1992 (July). "Genetic Algorithms," Scientific American,
267, pp. 66-72.
(If you are not familiar with the Prisoner's
Dilemma, read Robert Axelrod, 1984. The Evolution of Cooperation, New
York, Basic Books, pp. 3-69 and 158-68.)
Riolo,
Rick L., 1992 (July). “Survival of the Fittest Bits,” Scientific American,
267, pp. 89-91.
Axelrod, Robert, "The Evolution
of Strategies in the Iterated Prisoner's Dilemma," 1987. In Lawrence Davis (ed.), Genetic
Algorithms and Simulated Annealing, London: Pitman, and Los Altos, CA:
Morgan Kaufman, pp. 32-41. Reprinted in
Robert Axelrod, The Complexity of Cooperation: Agent-Based Models of
Competition and Collaboration, 1997. Princeton, NJ: Princeton University
Press, pp. 11-29.
6. Competition. October 9.
Exercise
4 due.
Cederman, Lars-Erik, 2001.
"Nationalist Systems Change and its Geographic Consequences,” Paper prepared for the Annual Meeting of the
American Political Science Association, San Francisco., August 30-September 2,
2001. Note: You may skim the appendix.
Kollman,
Ken, John H. Miller and Scott E. Page, 1998. “Political Parties and Electoral
Landscapes,” British Journal of
Political Science, 28, pp. 139-58. Available at http://proquest.umi.com/pqdweb
7.
Evolution and Reputation, October 16.
Lindgren,
Kristian, 1991. "Evolutionary Phenomena in Simple Dynamics," in C. G.
Langton et al. (eds.), Artificial Life II, Reading, MA: Addison-Wesley.
Henrich,
Joseph, et al., May 2001. “In search of homo economicus: Behavioral
experiments in 15 small-scale societies,” The American Economic Review, 91 ( 2001), pp 73-78.
Nowak,
Martin A., Karen M. Page, and Karl Sigmund, 8 September 2000. “Fairness Versus
Reason in the Ultimatum Game,” Science, 289, pp. 1773-75. Available from http://www.sciencemag.org/
Good example of evolutionary dynamics to explain human behavior in a simple
game, with and without reputational effects.
8.
Cascades. October 23.
Farmer,
J. Doyne, and Andrew W. Lo, 1999. “Frontiers of Finance: Evolution and Efficient
Markets,” Proc. Nat. Acad. Sci. USA, 96. pp. 1991-2. http://www.pnas.org/cgi/reprint/96/18/9991.pdf
Arthur, Brian W., John H. Holland, Blake
LeBaron, Richard Palmer and Paul Thayer, 1997. “Asset Pricing Under Endogenous
Expectations in an Artificial Stock Market,” in B. Arthur, S. Durlauf and D.
Lane (eds.), The Economy as an Evolving Complex System, II, Reading, MA:
Addison-Wesley, pp. 15-44. The source
code is available at http://ArtStkMkt.sourceforge.net
Arthur, W. Brian, 1988. "Urban
Systems and Historical Path Dependence," in Jese H. Ausubel and Robert
Herman (eds.), Cities and Their Vital Systems. Washington DC: National
Academy Press, pp. 85-97.
9.
Complexity. October 30.
Research design is due.
Resnick,
Mitchel 1994. Turtles, Termites, and
Traffic Jams: Explorations in Massively Parallel Microworlds, Cambridge,
MA: MIT Press, pp. 129-144 on
decentralized mind set.
Gell-Mann,
Murray, 1995. "What is Complexity?" Complexity, 1, pp.
16-19 on measuring the degree of complexity in a system.
Arthur,
W. Brian. 1993. "Why Do Things Become More Complex?", Scientific
American, May, p 144.
Holland,
John, 1995. Hidden Order. Reading, MA: Addison-Wesley, pp. 1-40 on
elements of a complex adaptive system.
Kelly,
Kevin, 1994. Out of Control: The New Biology of Machines, Social Systems,
and the Economic World. Reading,
MA: Addison-Wesley, pp. 22-25 and 468-72.
10-12.
Class reports. November 6, 13, and 20.
13.
Overview. December 4.
Project
report is due noon December 15.
Optional Readings
Introduction
to Complexity Theory. Week 1.
Waldrop, M. Mitchell, Complexity: The Emerging Science at the Edge of Order and Chaos. Touchstone
Books. 1993.
Kelly, Kevin, Out of Control.
Addison Wesley, 1996.
Axelrod, Robert and Michael Cohen, Harnessing
Complexity. Free Press, 2000.
Johnson, Steven, Emergence: The
Connected Lives of Ants, Brains, Cities and Software. Scribner, 2001.
Watts, Duncan J. Six Degrees: The
Science of a Connected Age, W.W. Norton & Company, 2003.
Agent-Based
Modeling. Week 2.
Tesfatsion,
Leigh (1997) ``How Economists Can Get A-Life'' in The Economy as a Complex
Evolving System II W. Brian Arthur, Steven Durlauf, and David Lane eds. pp
533-565. Addison Wesley, Reading, MA.
Epstein,
Joshua M. and Robert A. Axtell, 1976, Growing Artificial Societies:
Social Science from the Bottom Up. Washington, DC: Brookings and Cambridge, MA:
MIT Press, especially pp. 1-53
and 94-137.
Gilbert, Nigel, 1999. “Simulation, A New Way of Doing
Science,” American Behavioral Scientist, 42, August, pp. 1485-87.
An introduction to a special issue of useful articles.
Adaptive
Agents, Intelligence, and Emergent Human Organization: Capturing Complexity
through Agent-Based Modeling. A special issue of Proc. Natl. Acad. Sci. USA,
Vol. 99 (Supp. 3). May 14 2002, http://www.pnas.org/content/vol99/suppl_3/
Organization
Theory. Week 3.
March,
James G. 1978. "Bounded Rationality, Ambiguity, and the Engineering of
Choice," Bell Journal of Economics, 9, pp. 587-607.
Cohen,
Michael D., James G. March and Johan P. Olsen, 1972. "A Garbage Can Model
of Organizational Choice," Administrative Science Quarterly, 17,
pp. 1-25.
Carley,
Kathleen, 1991. "A Theory of Group Stability," American
Sociological Review, 56, pp. 331-54.
Axelrod,
Robert and Michael D. Cohen, 2000. Harnessing Complexity: Organizational
Implications of a Scientific Frontier (NY: Free Press).
Carpenter, Daniel, David Lazer, and
Kevin Esterling, “The Strength of Strong Ties: A Model of Contract Making in
Policy Networks with Evidence from U.S. Health Policies,” Rationality and Society, forthcoming.
Social
Influence. Week 4.
Axelrod,
Robert, 1997. "The Dissemination of Culture: A Model with Local
Convergence and Global Polarization," Journal of Conflict Resolution,
41, pp. 203-26. Reprinted in
Robert Axelrod, The Complexity of Cooperation: Agent-Based Models of Competition
and Collaboration, 1997. Princeton, NJ: Princeton University Press, pp.
145-77. For source code in Pascal see http://pscs.physics.lsa.umich.edu/Software/CC/CC7.html
Axtell,
Robert, Joshua Epstein, and H. Peyton Young, “The Emergence of Classes in a
Multi-Agent Bargaining Model,” Center for
Social and Economic Dynamics, Washington, D. C. Working Paper 9. The paper and the model itself are available
at http://www.brook.edu/ES/dynamics/papers/classes/
Gaylord,
Richard J. and Louis J. D’Andria, 1998. Simulating Society: A Mathematica
Toolkit for Modeling Socioeconomic Behavior (NY: Springer). (The
Mathematica source codes are available at http://www.telospub.com/catalog/FINANCEECON/SimSoc.html
for programs related to Axelrod’s culture model.)
Latane,
Bibb, Andrzej Nowak and James H. Liu. 1994. "Measuring Emergent Social
Phenomena: Dynamism, Polarization and Clustering as Order Parameters of Social
Systems," Behavioral Science, 39, p. 1-24.
Granovetter,
Mark, 1978. "Threshold Models of Collective Behavior," American
Sociological Review, 83, pp. 1420-42.
(This is an example of a formal model that does not require agent-based
techniques to solve.)
Lustig, Ian, “Agent-based modeling
of collective identity: testing constructivist theory,“ Journal of
Artificial Societies and Social Simulation vol. 3, no. 1. Available at http://jasss.soc.surrey.ac.uk/3/1/1.html
Rilling,
J. K., Gutman, D. A., Zeh, T. R., Pagnoni, G., Berns, G. S., & Kilts, C. D.
(2002). A Neural Basis for Social Cooperation. Neuron, 35, 395-405. See also NY Times story by N. Angier on this
research, July 23, 2002.
Genetic
Algorithm and Prisoner's Dilemma. Week 5.
Riolo,
Rick, 1992. "Survival of the Fittest," Scientific American,
July, pp. 114-6 on how to make your own genetic algorithm.
Morikawa,
Tomonori, John Orbell and Audun S. Runde, 1995. "The Advantage of Being
Moderately Complex," American
Political Science Review, 89, pp. 601-11. (On achieving cooperation even in one move Prisoner's Dilemmas
through local interaction.)
Axelrod,
Robert, 1997. Complexity of Cooperation, Chapter 3 on coping with
misperception and misunderstandings in the iterated Prisoner’s Dilemma.. For
source code in Fortran, including all of the rules submitted to the second
round of the computer tournament, see http://pscs.physics.lsa.umich.edu/Software/CC/CC2.html
Lindgren,
Kristian and Mats G. Nordahl, “Cooperation and Community Structure in
Artificial Ecosystems,” in Chris Langton (ed.), Artificial Life: An Overview
(Cambridge, MA: MIT Press, 1995), pp. 15-37. (Includes spatial PD, explicit
resource flows, predatory interactions, and food webs.)
Holland,
John H,. Hidden Order: How Adaptation Builds Complexity. The MIT
Press, 1995.
Cohen, Michael D., Rick L. Riolo,
and Robert Axelrod, 2001. “The Role of Social Structure in the Maintenance of
Cooperative Regimes,” Rationality and Society, 13, pp. 5-32.
Competition.
Week 6.
Johnson, Paul E., 1999. “Simulation in Political Science,” American
Behavioral Scientist, 42, pp. 1509-30.
Epstein,
Joshua, John D. Steinbruner, and Miles
T. Parker, 2001. “Modeling Civil Violence: An Agent-Based Computational
Approach,” Center for Social and Economic Dynamics, Washington, D. C. Working
Paper 20. http://www.brook.edu/es/dynamics/papers/cviolence/cviolence.htm
Kollman, Ken, John H. Miller, and Scott E. Page, 1992.
"Adaptive Parties in Spatial Elections," American Political
Science Review, 86, pp. 929-37
Cederman,
Lars-Erik, 1997. Emergent Actors in World Politics: How States and Nations
Develop and Dissolve. (Princeton, NJ: Princeton University Press),
especially pp. 184-212 and 219-22.
Cederman,
Lars-Erik, “Back to Kant: Reinterpreting the Democratic Peace as a
Macrohistorical Learning Process. American Political Science Review,
1995, vol. 95, pp 5-31.
Bremer,
Stuart A. and Michael Mihalka. 1977. "Machiavelli in Machina: Or Politics
among Hexagons," in Karl W. Deutsch et al. (eds.)., Problems of
World Modeling. Cambridge, MA: Ballinger, pp. 303-337.
Cusack,
Thomas R. and Richard Stoll. 1990. Exploring Realpolitik: Probing
International Relations Theory with Computer Simulation. Boulder, CO: Lynne
Rienner.
Schrodt,
Philip, "Conflict as a Determinant of Territory," Behavioral
Science, 26, 1981, pp. 37-50.
Cederman,
Lars-Erik, 1994. "Emergent Polarity: Analyzing State-Formation and Power
Politics," International Studies Quarterly, 38, especially
pp. 501-33.
Axelrod,
Robert, 1995. "A Model of the Emergence of New Political Actors" in
Nigel Gilbert and Rosaria Conte (eds.), Artificial Societies: The Computer
Simulation of Social Life. London: University College Press, 1995, pp.
19-39. Reprinted in Robert Axelrod, The Complexity of Cooperation:
Agent-Based Models of Competition and Collaboration, 1997. Princeton, NJ:
Princeton University Press, pp. 121-144.
For source code in Pascal see
http://pscs.physics.lsa.umich.edu/Software/CC/CC6.html
Kollman, et al., 1997. “Political Institutions and Sorting in a Tiebout
Model,” The American Economic Review, 87, pp. 977ff.
Evolution and Reputation. Week 7.
Riolo,
Rick L. Michael D. Cohen, and Robert Axelrod, 22 November 2001. “Evolution of
Cooperation without Reciprocity,”, Nature, 414.
Ferriere,
Regis, 11 June1998. “Help and You Shall Be Helped,” Nature, 393,
pp. 517-9.
Nowak,
Martin A. and Karl Sigmund, 11 June 1998. “Evolution of Indirect Reciprocity by
Image Scoring,” Nature, 393, pp. 573-7.
Cascades.
Week 8.
LeBaron, Blake, 2000.
“Agent-Based Computational Finance: Suggested Readings and Early Research,” Journal
of Economic Dynamics & Control, 24, pp. 679-702.
Ray J. Paul,
George M. Giaglis, and Vlatka Hlupic, 1999. “Simulation of Business Processes,”
American Behavioral Scientist, 42, pp. 1551-76.
Sargent,
Thomas, 1993. Bounded Rationality in Macroeconomics. Oxford: Clarendon
Press.
Palmer, R.G. , W. B. Arthur, H. Holland et al,. ”Artificial Economic Life- A Simple Model of the Stock Market." Physica D. 75 (1-3): 264-274 Aug. 1, 1994. See also articles that cite this article for additional stock market models.
Lux T., and M. Marchesi, “Scaling and Criticality
in a Stochastic Multi-Agent Model of a Financial Model,” Nature, 397
(6719): 498-500, Feb. 11, 1999. See also articles that cite this article for
additional stock market models.
Albin,
Peter and Duncan K. Foley, 1992. "Decentralized, Dispersed Exchange
Without and Auctioneer: A Simulation Study," Journal of Economic Behavior and Organization, 18,
pp. 27-51.
Krugman,
Paul, 1993. "On the Number and Location of Cities," European
Economic Review, 37, pp. 293-8.
Arthur,
W. Brian, 1995. "Complexity in Economic and Financial Markets," Complexity,
1, pp. 20-25.
Lesourne,
Jacques, 1992. The Economics of Order and Disorder: The Market as Organizer
and Creator. Oxford: Clarendon Press.
. Lohmann,
Susanne, 1994. “The Dynamics of Information Cascades: The Monday Demonstrations
in Leipzig, East Germany, 1989-91,” World Politics, 47, p.
42-101.
Complexity.
Week 9.
A. Meaning of Complexity
Waldrop,
Mitchell, 1992. Complexity: the Emerging Science at the Edge of Order and
Chaos. New York: Simon and Schuster on the evolution of chaos theory into complexity theory, some
applications to social sciences, and the history of the Santa Fe Institute.
Holland,
John H., 1995. Hidden Order, rest of book.
Holland,
John H., 1998. Emergence: From Chaos to Order (Reading, MA: Addison-Wesley).
Gell-Mann,
Murray, 1994. The Quark and the Jaguar: Adventures in the Simple and the
Complex. New York: Freeman.
Lansing,
Stephen, and James Kremer, 1993. "Emergent Properties of Balinese Water
Temple Networks: Coadaptation on a Rugged Fitness Landscape," American
Anthropologist, 95, pp.. 97-114.
B.
Fitness Landscapes
Kauffman,
Stuart, 1995. At Home in the Universe: The Search for Laws of
Self-Organization and Complexity, New York and Oxford: Oxford University
Press, pp. 169-75 on background on his N-K landscapes.
Axelrod,
Robert and D. Scott Bennett, 1993. "A Landscape Theory of
Aggregation", British Journal of Political Science, 23, pp. 211-33. . Reprinted in Robert Axelrod, The Complexity of Cooperation:
Agent-Based Models of Competition and Collaboration, 1997. Princeton, NJ:
Princeton University Press, pp. 69-94.
For source code in Pascal and raw data see
http://pscs.physics.lsa.umich.edu/Software/CC/CC4.html
Axelrod, Robert, Will Mitchell, Robert E. Thomas, D. Scott Bennett, and
Erhard Bruderer, 1995. "Coalition Formation in Standard-Setting
Alliances,", Management Science, 41, pp. 1493-1508.
Reprinted in Robert Axelrod, The Complexity of Cooperation: Agent-Based
Models of Competition and Collaboration, 1997. (Princeton, NJ: Princeton
University Press). This is another test of Axelrod and Bennett’s landscape
model. For source code in Pascal and raw data see http://pscs.physics.lsa.umich.edu/Software/CC/CC5.html
“Cousins”
of Complexity.
Gleick,
James, Chaos: Making a New Science, 1987. New York and London: Penguin Books, pp. 1-31, and 98-9.
Crutchfield,
James P. et al., 1986. "Chaos," Scientific American, 255,
December, pp. 46-57.
Williams,
Garnett P. 1997. Chaos Theory Tamed, Washington, DC: Joseph Henry Press,
1997, pp. 161-73. On the logistic equation and control parameters.
B.
Self-Organized Criticality
Bak,
Per and Kan Chen, January 1991. "Self-Organized Criticality," Scientific
American, pp. 46-53.
Bak,
Per. 1996. How Nature Works: The
Science of Self-Organized Criticality. New York: Springer-Verlag, pp. 1-32,
135-43, and 183-92.
C.
Cellular Automata
Callahan,
Paul, “What is the Game of Life?” http://www.math.com/students/wonders/life/life.html (Read the text, and run the simulations, and
study the R-pentomino.) An example of a
cellular automata, in contrast to an agent-based model.
Wolfram,
Stephen, A New Kind of Science, 2002. Campaign, IL: Wolfram Media.
D. Neural Nets
Coveney,
Peter and Roger Highfield, 1995. Frontiers of Complexity: the Search for
Order in a Chaotic World, New York: Fawcett Columbine, pp. 130-149 on
neural nets.
Bailey,
James, 1996. After Thought: The Computer Challenge to Human Intelligence. New York: Basic Books, pp. 127-35.
Chellapilla,
Kumar and David B. Fogelm September 1999, “Evolution, neural networks, games,
and intelligence.” Proceedings of the IEEE, 87(9):1471--1496.
Books
on Agent-Based Modeling
(For books on this and related sub
see http://www.econ.iastate.edu/tesfatsi/sylalife.htm
)
Axelrod,
Robert, 1997. Complexity of Cooperation, Princeton, NJ: Princeton
University Press. Chapters on seven models, each with an introduction about
their origin and reception.
Bonabeau,
Eric, Marco Dorigo, and Guy Theraulaz, 1999. Swarm Intelligence: From
Natural to Artificial Systems, Oxford: Oxford University Press.
Casteelfranchi,
Cristiano and Eric Werner (eds.), 1994. Artificial Social Systems,
Berlin and New York: Springer-Verlag.
Conte,
Rosario Rainer Hegselmann and Pietro Terna (eds.), 1997. Simulating Social
Phenomena. Berlin: Springer.
E.
Hillebrand and J. Stender (eds.), 1994. Many-Agent Simulation and Artificial
Life. Amsterdam, Oxford and Washington: IOS Press.
Gilbert,
Nigel and Rosaria Conte (eds.), 1995. Artificial
Societies: the Computer Simulation of Social Life. London: UCL Press.
Gilbert,
Nigel and Jim Doran (eds.), 1994. Simulating Societies: The Computer
Simulation of Social Phenomena. London: UCL Press.
Gumerman,
George (eds.), 1994. Understanding
Complexity in the Prehistoric Southwest.
Reading, MA: Addison-Wesley.
Schelling,
Thomas, 1978. Micromotives and Macro Behavior, NY: Norton.
Sigmund,
Karl. 1993. Games of Life: Explorations in Ecology, Evolution, and Behavior.
Oxford: Oxford University Press.
Web
Sites
A. Complexity News
Complexity
Digest is a weekly report covering all aspects of complexity. It typically has
abstracts of about 20 articles, as well as news about conferences and
opportunities. You can read it on-line at
http://www.comdig.org/ or
you can have it e-mailed to you each week.
B. Reference material
1.Leigh
Tesfatsion maintains a very comprehensive site for agent-based modeling in the
social sciences. It includes a list of interested faculty, on-line journals,
concepts
http://www.econ.iastate.edu/tesfatsi/ace.htm
2.
Material on evolutionary theories in the social sciences: http://etss.net/
3.
Special issues of The Computational Economics and The Journal of
Economic Dynamics and Control are devoted to agent-based models.
Their introductions are available at http://www.econ.iastate.edu/tesfatsi/surveys.htm#ACEspec
4.
Annotated bibliography of Prisoner's Dilemma research: http://pscs.physics.lsa.umich.edu/RESEARCH/Evol_of_Coop_Bibliography.html
5.
A web-based journal is Journal of Artificial Societies and Social Simulation
at http://jasss.soc.surrey.ac.uk/JASSS.html
C.
Opportunities
1. UM’s Center for the Study of
Complexity has many local activities.
2.
Many national and international
workshops and meetings on complexity are available. See http://www.econ.iastate.edu/tesfatsi/cfp.htm or the Complexity Digest http://www.comdig.org/
3.
The Santa Fe Institute is the world center for the study of complexity. See http://www.santafe.edu/index.html For example, each summer SFI offers
intensive programs for advanced graduate students. One is for all fields (application deadline has been in January
of each year), and one is specifically for economic and closely related fields,
the Santa Fe Graduate Workshop in Economics (application deadline not yet set,
but Professor Scott Page of UM should know the details).
4.
The Society of Computational Economics sponsors an annual contest for
outstanding research manuscripts in computational economics written by graduate
students. The contest is open to graduate students worldwide working on any
aspect of computational economics. See http://wuecon.wustl.edu/sce.
D. Specific Models
1.
Documentation and source code of material in Axelrod's Complexity of
Cooperation: http://pscs.physics.lsa.umich.edu/Software/ComplexCoop.html
2.
Mathematica source code from Gaylord, Richard J. and Louis J. D’Andria, 1998. Simulating
Society: A Mathematica Toolkit for Modeling Socioeconomic Behavior (NY): www.telospub.com
3. Runnable models (with source code
in Java):
a.
from Brookings’ Center on Social and Economic Dynamics using Ascape. This includes
many models. Some of these will be described in the Dec. 2001 issue of Atlantic
Monthly. See http://www.brook.edu/es/dynamics/models/ascape/
b.
from University of Chicago group, using RePast. This includes Epstein and
Axtell’s sugarscape model: http://repast.sourceforge.net/
c.
from Marshall Van Alstyne, School of Information, University of Michigan, an
information diffusion simulator for agent societies. It includes tutorials on
several works by March and by Watts. It just requires Java running under
IE. www.si.umich.edu/~mvanalst/iShare
d. Axtell, “The Emergence of Firms in a
Population of Agents: Local Increasing Returns, Unstable Nash Equilibria, and
Power Law Size Distributions,” Brooking Institutions, CSED Working Paper No. 3,
June 1999. A commentary in Nature is at http://www.nature.com/nsu/010913/010913-2.html The paper itself with a Java simulation is
at http://www.brook.edu/dybdocroot/es/dynamics/papers/firms/firmspage.htm.