Skip to main content

Agent-Based Computational Economics: Overview and Brief History

  • Chapter
  • First Online:
Artificial Intelligence, Learning and Computation in Economics and Finance

Part of the book series: Understanding Complex Systems ((UCS))

Abstract

Scientists and engineers seek to understand how real-world systems work and could work better. Any modeling method devised for such purposes must simplify reality. Ideally, however, the modeling method should be flexible as well as logically rigorous; it should permit model simplifications to be appropriately tailored for the specific purpose at hand. Flexibility and logical rigor have been the two key goals motivating the development of Agent-based Computational Economics (ACE), a completely agent-based modeling method characterized by seven specific modeling principles. This perspective provides an overview of ACE, a brief history of its development, and its role within a broader spectrum of experiment-based modeling methods.

This ACE perspective, based in part on Tesfatsion (2017, 2021b, 2022a), is an invited chapter for: R. Venkatachalam (Ed.), 2022. Artificial Intelligence, Learning and Computation in Economics and Finance, Springer, to appear. A preprint version of this ACE perspective is posted at the ISU Digital Repository as Economics Working Paper #21004; see Tesfatsion (2022j).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    An initial-value state-space model is a state-space model for a dynamic system S that runs forward through time, commencing at some specified start-time \(t^{o}\), with all boundary conditions taking the form of constraints on the state of S at the start-time \(t^{o}\).

  2. 2.

    This essay was brought to my attention circa 1985 by Bob Rider, a Ph.D. student in the Department of Economics at the University of Southern California with an interest in game theory.

  3. 3.

    As indicated by a preserved sign-up sheet, the participants in this informal meeting were: Rob Axtell; Ann Bell; Chris Birchenhall; Kai Brandt; Thomas Brenner; Charlotte Bruun; Shu-Heng Chen; Michael Gordy; Sergei Guriev; Armin Haas; Esther Hauk; Gillioz Jean-Blaise; Alan Kirman; Bob Marks; Christian Rieck; Ernesto Somma; Leigh Tesfatsion; and Nick Vriend.

  4. 4.

    Netscape Communications Corporation, founded in April 1994 by Marc Andreessen and James H. Clark, released Netscape Navigator in November 1994 as freely downloadable software. Netscape Navigator, a successor of Mosaic (co-developed by Andreesen), was among the first browser products released in support of the mid-1990s consumer Internet revolution.

  5. 5.

    The earliest distributed ABM/ACE news notes were not saved in retrievable form; the online posted ACE news notes (Tesfatsion 2022b) begin in February 1997. The formatting of these online ACE news notes is ancient by browser standards. Although some formatting commands used in these news notes no longer compile properly using modern browsers, the news notes have been left in their originally posted form in order to preserve their historical authenticity.

  6. 6.

    Specifically, to reflect the name change from ABE to ACE, the website URL address was changed from http://www.econ.iastate.edu/tesfatsi/abe.htm to http://www.econ.iastate.edu/tesfatsi/ace.htm, and the mailing list address was changed from abelist@iastate.edu to acenewslist@iastate.edu.

  7. 7.

    The annual SCE meeting is officially referred to as the International Conference on Computing in Economics and Finance (CEF).

  8. 8.

    These welcoming economic journals include: Computational Economics; International J. of Microsimulation; J. of Economic Behavior and Organization; J. of Economic Dynamics and Control; J. of Economic Interaction and Coordination; and J. of Evolutionary Economics. For a more extensive linked listing of welcoming journals, including finance and game theory journals, see Tesfatsion (2022c).

References

  • Arthur WB (2021) Foundations of complexity economics. Nat Rev Phys 3:136–145. https://doi.org/10.1038/s42254-020-00273-3

  • Axelrod R (1984) The evolution of cooperation. Basic Books Inc, New York

    Google Scholar 

  • Axtell RL, Farmer JD (2022) Agent-based modeling in economics and finance: past, present, and future, Journal of Economic Literature, to appear

    Google Scholar 

  • Battula S, Tesfatsion L (2020) Agent-based modeling of electricity systems (AMES) - version 5.0. Github code/data repository, Battelle Memorial Institute. https://github.com/ames-market/AMES-V5.0

  • Chen S-H (2012) Varieties of agents in agent-based computational economics: a historical and an interdisciplinary perspective. J Econ Dyn Control 36(1):1–25

    Google Scholar 

  • Chen S-H (2016) Agent-based computational economics: how the idea originated and where it is going. Routledge, New York

    Google Scholar 

  • Chen S-H (ed) (2002) Evolutionary computation in economics and finance. Physica-Verlag, Heidelberg

    Google Scholar 

  • Chen S-H, Li S-P (2012) Econophysics: bridges over a turbulent current. Int Rev Financ Anal 23:1–10

    Google Scholar 

  • Chen S-H, Yeh C-H (2001) Evolving traders and the business school with genetic programming: a new architecture of the agent-based artificial stock market. J Econ Dyn Control 25(3–4):363–393

    Article  MATH  Google Scholar 

  • Dawid H, Delli Gatti D (2018) Agent-based macroeconomics, Chapter 2. In: Hommes C, LeBaron B (eds) Handbook of computational economics 4: heterogeneous agent modeling. Handbooks in economics series, North Holland (Elsevier), Amsterdam, pp 63–156

    Google Scholar 

  • Dosi G, Roventini A (2019) More is different ... and complex! the case for agent-based macroeconomics. J Evolut Econ 29:1–37. https://doi.org/10.1007/s00191-019-00609-y

  • Epstein JM (2006) Generative social science: studies in agent-based computational modeling. Princeton University Press, Princeton

    MATH  Google Scholar 

  • Epstein JM, Axtell RL (1996) Growing artificial societies: social science from the bottom up. The MIT Press, Cambridge

    Book  Google Scholar 

  • Gallegati M (2018) Complex agent-based models. New economic windows series, Springer International, Switzerland

    Google Scholar 

  • Hofstadter DR (1983) Metamagical themas: computer tournaments of the Prisoner’s Dilemma suggest how cooperation evolves. Sci Am 248(5):16–26

    Article  ADS  Google Scholar 

  • Judd KL (2006) Computationally intensive analyses in economics, chapter 17. In: Tesfatsion L, Judd KL (eds) Handbook of computational economics 2: agent-based computational economics. Handbooks in economics series, North Holland (Elsevier), Amsterdam, pp 881–893

    MATH  Google Scholar 

  • Kalaba RE, Tesfatsion L (1991) Solving nonlinear equations by adaptive homotopy continuation. Appl Math Comput 41(2):Part II:99–115

    Google Scholar 

  • Kirman A (2011) Complex economics: individual and collective rationality. The Graz Schumpeter lectures, Routledge, New York

    Google Scholar 

  • LeBaron B, Tesfatsion L (2008) Modeling macroeconomies as open-ended dynamic systems of interacting agents. Am Econ Rev (Pap Proc) 98(2):246–250

    Google Scholar 

  • Lori G, Porter J (2018) Agent-based modeling for financial markets. In: Chen S-H, Kaboudan M, Du Y-R (eds) The Oxford handbook of computational economics and finance. Oxford handbooks online. Oxford University Press, Oxford

    Google Scholar 

  • Rahmandad H, Sterman J (2008) Heterogeneity and network structure in the dynamics of diffusion: comparing agent-based and differential equation models. Manag Sci 54(5):998–1014

    Article  Google Scholar 

  • Railsback SF, Grimm V (2019) Agent-based and individual-based modeling, 2nd edn. Princeton University Press, Princeton

    Google Scholar 

  • Richiardi M (2013) The missing link: agent-based models and dynamic microsimulation, chapter 1. In: Leitner S, Wall F (eds) Artificial economics and self organization: agent-based approaches to economics and social systems, Springer Lecture Notes in Economics and Mathematical Systems 669, Berlin, Germany, pp 3–15

    Google Scholar 

  • Rovelli C (2018) The order of time. Riverhead Books, New York, English translation by Simon Carnell and Erica Segre

    Google Scholar 

  • Ryle G (1949) The concept of mind. Hutchinson, London

    Google Scholar 

  • Sinitskaya E, Tesfatsion L (2015) Macroeconomies as constructively rational games. J Econ Dyn Control 61:152–182

    Article  MathSciNet  MATH  Google Scholar 

  • Smolin L (2007) The trouble with physics: the rise of string theory, the fall of science, and what comes next. Houghton Mifflin, Boston

    Google Scholar 

  • Tesfatsion L (2001a) Introduction to the special double issue on agent-based computational economics. J Econ Dyn Control 25(3–4):281–293

    Google Scholar 

  • Tesfatsion L (2001b) Introduction to the special issue on agent-based computational economics. Comput Econ 18(1):1–8

    Google Scholar 

  • Tesfatsion L (2001c) Guest editorial: agent-based modeling of evolutionary economic systems. IEEE Trans Evolut Comput 5(5):437–441

    Google Scholar 

  • Tesfatsion L (2001d) Structure, behavior, and market power in an evolutionary labor market with adaptive search. J Econ Dyn Control 25(3–4):419–457

    Google Scholar 

  • Tesfatsion L (2017) Modeling economic systems as locally-constructive sequential games. J Econ Methodoly 24(4):384–409

    Google Scholar 

  • Tesfatsion L (2018) Electric power markets in transition: agent-based modeling tools for transactive energy support, chapter 13. In: Hommes C, LeBaron B (eds) Handbook of computational economics 4: heterogeneous agent models. Handbooks in economics series. North Holland (Elsevier), Amsterdam, pp 715–766

    Google Scholar 

  • Tesfatsion L (2021a) A new swing-contract market design for wholesale power markets. IEEE press series on power engineering. Wiley Inc, Hoboken

    Google Scholar 

  • Tesfatsion L (2021b) Agent-based modeling: the right mathematics for social science? Keynote address. In: 16th annual social simulation conference (virtual), Sponsored by the European social simulation association (ESSA), September 20–24. https://www2.econ.iastate.edu/tesfatsi/CompleteABM.SSC2021Keynote.LTesfatsion.pdf

  • Tesfatsion L (2022a) Agent-based computational economics (ACE): homepage. https://www2.econ.iastate.edu/tesfatsi/ace.htm

  • Tesfatsion L (2022b) ACE distributed news notes (1997–2017). https://www2.econ.iastate.edu/tesfatsi/acepast.htm

  • Tesfatsion L (2022c) ACE resource site: journal and publisher information. https://www2.econ.iastate.edu/tesfatsi/publish.htm

  • Tesfatsion L (2022d) Empirical validation and verification of agent-based models. https://www2.econ.iastate.edu/tesfatsi/empvalid.htm

  • Tesfatsion L (2022e) Learning and the embodied mind. https://www2.econ.iastate.edu/tesfatsi/aemind.htm

  • Tesfatsion L (2022f) Agent-based macroeconomics. https://www2.econ.iastate.edu/tesfatsi/amulmark.htm

  • Tesfatsion L (2022g) Agent-based financial economics. https://www2.econ.iastate.edu/tesfatsi/afinance.htm

  • Tesfatsion L (2022h) Agent-based electricity market research. https://www2.econ.iastate.edu/tesfatsi/aelect.htm

  • Tesfatsion L (2022i) Mixed experiments with real and computational agents. https://www2.econ.iastate.edu/tesfatsi/aexper.htm

  • Tesfatsion L (2022j) Agent-based computational economics: overview and brief history, economics working paper #21004, ISU digital repository (Originally posted 3/2021; Latest revision 5/2022), Iowa State University, Ames, IA 50011-1054. https://lib.dr.iastate.edu/econ_workingpapers/126

  • Tesfatsion L, Judd KL (eds) (2006) Handbook of computational economics 2: agent-based computational economics. Handbooks in economics series. North Holland (Elsevier), Amsterdam

    Google Scholar 

  • Wilensky U, Rand W (2015) An introduction to agent-based modeling. MIT Press, Cambridge, MA, USA

    Google Scholar 

  • Zheng RZ, Gardner MK (eds) (2017) Handbook of research on serious games for educational purposes. IGI Global, Hershey, PA, USA

    Google Scholar 

Download references

Acknowledgements

I am very grateful to Shu-Heng Chen, Marcin Czupryna, and Volker Grimm for their extensive thoughtful comments on a previous version of this perspective. I am also thankful to the following people for helpful comments on related topics, many directed specifically to my coverage of these related topics in Tesfatsion (2021b): Richie Adelstein; W. Brian Arthur; Bob Axelrod; Rob Axtell; Costas Azariadis; Ross Baldick; Cesar Enrique Garcia Diaz; Marty Eichenbaum; Dan Friedman; Mauro Gallegati; Nick Gotts; Omar Guerrero; Dirk Helbing; Mike Honig; Dan Houser; Marco Janssen; George Judge; Lorenzo Kristov; Sergio Mariotti; Sheri Markose; Bob Marks; Vittorio Nespeca; Dawn Parker; Gary Polhill; Steve Railsback; Ryan Schoppe; Rajiv Sethi; Ken Steiglitz; Shyam Sunder; Peter Swann; Nick Vriend; Steve Widergren; and Mike Woodford.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Leigh Tesfatsion .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Tesfatsion, L. (2023). Agent-Based Computational Economics: Overview and Brief History. In: Venkatachalam, R. (eds) Artificial Intelligence, Learning and Computation in Economics and Finance . Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-031-15294-8_4

Download citation

Publish with us

Policies and ethics