Agent-Based Computational Economics (ACE)
and ACE-Related Topics

Last Updated: 24 April 2024

Site developed by:
Leigh Tesfatsion
Professor Emerita of Economics
Courtesy Professor of Electrical
    and Computer Engineering
Iowa State University
Ames, Iowa 50011-1070
tesfatsi AT

Agent-Based Computational Economics (ACE) Homepage

Site Disclaimer:
This surveys site has not been updated since 2007; it has been superceded by the more currently updated resource sites linked at the above ACE Homepage. However, it is retained here for possible historical interest.

Robert Axelrod and Leigh Tesfatsion, An On-Line Guide for Newcomers to Agent-Based Modeling in the Social Sciences (html,44KB).

This site provides web support materials (readings and demonstration software) for Robert Axelrod and Leigh Tesfatsion, "A Guide for Newcomers to Agent-Based Modeling in the Social Sciences" (pdf preprint, 46KB) , in Leigh Tesfatsion and Kenneth L. Judd (Eds.), Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics (Table of Contents,html), Handbooks in Economics Series, North-Holland, Amsterdam, Spring 2006, to appear.

Brookings Institution (Washington, D.C.) supports a website titled "The Road to Agent-Based Models" (html) that provides a brief history of agent-based modelling together with related web links.

John Duffy, "Review of Growing Artificial Societies: Social Science from the Bottom Up," Southern Economic Journal, Vol. 64, No. 3 (Jan. 1998), pp. 791-794.

John Hogan, "From Complexity to Perplexity" (html), Scientific American, Volume 272, June 1995, pages 74-79.

This controversial article is a rather cynical and caustic view of the research on complex systems undertaken at the Santa Fe Institute through the mid-1990s. At the very least, it provides a cautionary note to researchers regarding the dangers of over-hyping (by media commentators among others) of new and as-yet unproven methodologies related to the study of complex systems.

Blake LeBaron, "Agent Based Computational Finance: Suggested Readings and Early Research" (pdf preprint,153KB), Journal of Economic Dynamics and Control, Volume 24, Numbers 5-7, 2000, pages 679-702.

Abstract: This paper explores some of the early work in finance making use of computer simulated markets with individual adaptive agents. Six papers are summarized in detail, and references are given to many other studies in this wide-ranging research area. It also addresses many of the questions that new researchers will face when getting into the field.

Roger A. McCain (Drexel University, Philadelphia, Pennsylvania), a researcher active in ACE research, maintains a website titled Game Theory: An Introductory Sketch (html) that provides a readable elementary exposition of basic game theory principles for non-specialists.

Scott E. Page, "Computational Models from A to Z" (html), Keynote Address to SwarmFest'99, The Anderson School of Management at the University of California at Los Angeles, March 27-29, 1999.

Author's Abstract: "The growing use of computational models of social, physical and biological systems raises many questions and concerns. Platforms such as Swarm enable researchers to construct detailed, robust computational models. The availability of Swarmlike platforms will speed the pace of the computational revolution and open new areas of research. In this brief tongue-in-cheek overview, I discuss twenty-six topics pertaining to these computational models. Unbelievably, each of the twenty-six subject headings begins with a different letter! Given this fortuitous fact, I have chosen to arrange the topics alphabeticaly. Though containing bits of levity, this paper should be read seriously both as a social scientist's commentary on a nascent field and as a guide to future research."

Leigh Tesfatsion, Agent-Based Computational Economics: A Constructive Approach to Economic Theory (pdf preprint,253KB), in Leigh Tesfatsion and Kenneth L. Judd (eds.), Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics (Preface, Contributors, and Abstracts), Handbooks in Economics Series, North-Holland, Amsterdam, 2006, 904pp.

Abstract: This chapter explores the potential advantages and disadvantages of Agent-Based Computational Economics (ACE) for the study of economic systems. General points are concretely illustrated using an ACE model of a two-sector decentralized market economy. Six issues are highlighted: Constructive understanding of production, pricing, and trade processes; the essential primacy of survival; strategic rivalry and market power; behavioral uncertainty and learning; the role of conventions and organizations; and the complex interactions among structural attributes, behaviors, and institutional arrangements.

Leigh Tesfatsion, "Economic Agents and Markets as Emergent Phenomena" (pdf preprint,167KB), Proceedings of the National Academy of Sciences U.S.A., Vol. 99 (supp. 3), 2002, pp. 7191-7192.

Abstract: A brief overview of recent work in agent-based computational economics is provided, with a stress on the research areas highlighted at the NAS Sackler Colloquium session "Economic Agents and Markets as Emergent Phenomena" held in October 2001 in Irvine, CA.

Leigh Tesfatsion, "Agent-Based Computational Economics: Growing Economies from the Bottom Up", Artificial Life, Volume 8, Number 1, 2002, 55-82, published by the MIT Press (pdf preprint,212KB).

Abstract: This study is an extended version of the previous PNAS overview. The main objectives and defining characteristics of agent-based computational economics (ACE) are outlined, and similiarities and distinctions between ACE and artificial life research are clarified. Eight ACE research areas are identified, and a number of publications in each area are highlighted for concrete illustration. Open questions and directions for future ACE research are also considered. The study concludes with a discussion of the potential benefits of the ACE approach, as well as some potential difficulties.

Leigh Tesfatsion, "Agent-Based Computational Economics: Modeling Economies as Complex Adaptive Systems", Information Sciences 149 (2003), 263-269 (pdf preprint,71KB).

This is an abbreviated version of the previously listed ACE survey appearing in Artificial Life in 2002 used as the supporting document for a presentation at the 2002 Joint Conference on Information Sciences (JCIS).

Leigh Tesfatsion, "Introduction to the Journal of Economic Dynamics and Control Special Issue on ACE", Volume 25, Numbers 3-4, March 2001, pp. 281-293 (pdf preprint,288KB).

Following a brief discussion of ACE, this introduction provides a synopses of the articles included in the JEDC special issue on ACE.

Leigh Tesfatsion, "Introduction to the Computational Economics Special Issue on ACE", Volume 18, Number 1, October 2001, pp. 1-8 (pdf preprint,236KB).

Following a brief discussion of ACE, this introduction provides a synopses of the articles included in the CE special issue on ACE.

Leigh Tesfatsion, "Guest Editorial for the special issue of the IEEE Transactions on Evolutionary Computation on Agent-Based Modelling of Evolutionary Economic Systems", Volume 5, Number 5, October 2001, pp. 437-441 (pdf preprint,278KB).

A brief overview of agent-based computational economics (ACE) is provided, followed by synopses of the articles included in the IEEE-TEC special issue on ACE. Additional readings are also suggested.

Leigh Tesfatsion, "Agent-Based Computational Economics: A Brief Guide to the Literature", in Jonathan Michie (ed.), Reader's Guide to the Social Sciences, Volume 1, Fitzroy-Dearborn, London, UK, March 2001 (pdf preprint,217KB).

Leigh Tesfatsion, "How Economists Can Get Alife", pp. 533-564 in W. Brian Arthur, Steven Durlauf, and David Lane (eds.), The Economy as an Evolving Complex System, II, Santa Fe Institute Studies in the Sciences of Complexity, Volume XXVII, Addison-Wesley, 1997 (pdf preprint,560KB).

Abstract: This study presents a summary overview of the basic artificial life (alife) paradigm, stressing aspects especially relevant for the study of decentralized market economies. In particular, recent work on a Trade Network Game (TNG) framework combining evolutionary game play with endogenous partner selection is used to illustrate how the alife paradigm might be specialized to economics. Analytical and simulation work is reported to show how the TNG is currently being used to study the evolutionary implications of alternative market structures at three different levels: individual trade behavior; trade network formation; and social welfare.

Leigh Tesfatsion, "How Economists Can Get Alife: An Abbreviated Version" (html).

This is a short summary of the previously cited article that appeared in Arthur et al. (1997). It includes updated references and updated website URLs.

Leigh Tesfatsion, "Review of J. M. Epstein and R. Axtell, Growing Artificial Societies: Social Science from the Bottom Up", Journal of Economic Literature XXXVI (March 1998), 233-234 (pdf preprint,28KB).

Nicolaas Vriend, Rational Behavior and Economic Theory, Journal of Economic Behavior and Organization, Volume 29, 1996,263-285.

This article argues that ACE models with adaptive agents fit in well with the standard economic concept of rationality.

Nicolaas Vriend, "Was Hayek an Ace?," Southern Economic Journal, 2002, Vol. 68, No. 4, pp. 811-840.

Note: See also Rudolphe Buda, "Propositions for the Building of a Quantitative Austrian Modeling: An Answer to Prof. Rizzo and Prof. Vriend" (pdf,648KB), Working Paper 2007-09, Université Paris-X-Nanterre.

Abstract: "In order to address the question whether F. A. Hayek might have been an Agent-Based Computational Economist (ACE) avant-la-lettre, an ACE model concerning the phenomenon of information contagion is considered. It is shown how information-contagious behavior can emerge in a coevolutionary process of interacting adaptive agents, how this is related to various Hayekian themes, and how ACE research in general is an application of Hayek's methodological insights."

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