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Agent-based computational economics (ACE) is the area of computational economics that studies economic processes, including whole economies, as dynamic systems of interacting agents. As such, it falls in the paradigm of complex adaptive systems.^[1] In corresponding agent-based models, the "agents" are "computational objects modeled as interacting according to rules" over space and time, not real people. The rules are formulated to model behavior and social interactions based on incentives and information.^[2] Such rules could also be the result of optimization, realized through use of AI methods (such as Q-learning and other reinforcement learning techniques).^[3]

The theoretical assumption of mathematical optimization by agents in equilibrium is replaced by the less restrictive postulate of agents with bounded rationality adapting to market forces.^[4] ACE models apply numerical methods of analysis to computer-based simulations of complex dynamic problems for which more conventional methods, such as theorem formulation, may not find ready use.^[5] Starting from initial conditions specified by the modeler, the computational economy evolves over time as its constituent agents repeatedly interact with each other, including learning from interactions. In these respects, ACE has been characterized as a bottom-up culture-dish approach to the study of economic systems.^[6]

ACE has a similarity to, and overlap with, game theory as an agent-based method for modeling social interactions.^[7] But practitioners have also noted differences from standard methods, for example in ACE events modeled being driven solely by initial conditions, whether or not equilibria exist or are computationally tractable, and in the modeling facilitation of agent autonomy and learning.^[8]

The method has benefited from continuing improvements in modeling techniques of computer science and increased computer capabilities. The ultimate scientific objective of the method is to "test theoretical findings against real-world data in ways that permit empirically supported theories to cumulate over time, with each researcher’s work building appropriately on the work that has gone before."^[9] The subject has been applied to research areas like asset pricing,^[10] competition and collaboration,^[11] transaction costs,^[12] market structure and industrial organization and dynamics,^[13] welfare economics,^[14] and mechanism design,^[15] information and uncertainty,^[16] macroeconomics,^[17] and Marxist economics.^[18]^[19]

Übersicht

The "agents" in ACE models can represent individuals (e.g. people), social groupings (e.g. firms), biological entities (e.g. growing crops), and/or physical systems (e.g. transport systems). The ACE modeler provides the initial configuration of a computational economic system comprising multiple interacting agents. The modeler then steps back to observe the development of the system over time without further intervention. In particular, system events should be driven by agent interactions without external imposition of equilibrium conditions.^[20] Issues include those common to experimental economics in general^[21] and development of a common framework for empirical validation ^[22] and resolving open questions in agent-based modeling.^[23]

ACE is an officially designated special interest group (SIG) of the Society for Computational Economics.^[24] Researchers at the Santa Fe Institute have contributed to the development of ACE.

Example: finance

One area where ACE methodology has frequently been applied is asset pricing. W. Brian Arthur, Eric Baum, William Brock, Cars Hommes, and Blake LeBaron, among others, have developed computational models in which many agents choose from a set of possible forecasting strategies in order to predict stock prices, which affects their asset demands and thus affects stock prices. These models assume that agents are more likely to choose forecasting strategies which have recently been successful. The success of any strategy will depend on market conditions and also on the set of strategies that are currently being used. These models frequently find that large booms and busts in asset prices may occur as agents switch across forecasting strategies.^[10]^[25]^[26] More recently, Brock, Hommes, and Wagener (2009) have used a model of this type to argue that the introduction of new hedging instruments may destabilize the market,^[27] and some papers have suggested that ACE might be a useful methodology for understanding the 2008 financial crisis.^[28]^[29]^[30] See also discussion under Financial economics § Financial markets and § Departures from rationality.

References

^ • W. Brian Arthur, 1994. "Inductive Reasoning and Bounded Rationality," American Economic Review, 84(2), pp. 406-411 Archived 21 May 2013 at the Wayback Machine.
• Leigh Tesfatsion, 2003. "Agent-based Computational Economics: Modeling Economies as Complex Adaptive Systems," Information Sciences, 149(4), pp. 262-268 Archived 26 April 2012 at the Wayback Machine.
^ Scott E. Page (2008). "agent-based models," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
^ Richard S. Sutton and Andrew G. Barto, Reinforcement Learning: An Introduction, The MIT Press, Cambridge, MA, 1998 [1] Archived 4 September 2009 at the Wayback Machine
^ • John H. Holland and John H. Miller (1991). "Artificial Adaptive Agents in Economic Theory," American Economic Review, 81(2), pp. 365-370 Archived 5 January 2011 at the Wayback Machine p. 366.
• Thomas C. Schelling (1978 [2006]). Micromotives and Macrobehavior, Norton. Description Archived 2 November 2017 at the Wayback Machine, preview.
• Thomas J. Sargent, 1994. Bounded Rationality in Macroeconomics, Oxford. Description and chapter-preview 1st-page links.
^ • Kenneth L. Judd, 2006. "Computationally Intensive Analyses in Economics," Handbook of Computational Economics, v. 2, ch. 17, Introduction, p. 883. [Pp. 881- 893. Pre-pub PDF.
• _____, 1998. Numerical Methods in Economics, MIT Press. Links to description Archived 11 February 2012 at the Wayback Machine and chapter previews.
^ • Leigh Tesfatsion (2002). "Agent-Based Computational Economics: Growing Economies from the Bottom Up," Artificial Life, 8(1), pp.55-82. Abstract and pre-pub PDF Archived 14 May 2013 at the Wayback Machine.
• _____ (1997). "How Economists Can Get Alife," in W. B. Arthur, S. Durlauf, and D. Lane, eds., The Economy as an Evolving Complex System, II, pp. 533-564. Addison-Wesley. Pre-pub PDF Archived 15 April 2012 at the Wayback Machine.
^ • Joseph Y. Halpern (2008). "computer science and game theory," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
• Yoav Shoham (2008). "Computer Science and Game Theory," Communications of the ACM, 51(8), pp. 75-79 Archived 26 April 2012 at the Wayback Machine.
• Alvin E. Roth (2002). "The Economist as Engineer: Game Theory, Experimentation, and Computation as Tools for Design Economics," Econometrica, 70(4), pp. 1341–1378.
^ Tesfatsion, Leigh (2006), "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," ch. 16, Handbook of Computational Economics, v. 2, part 2, ACE study of economic system. Abstract and pre-pub PDF.
^ • Leigh Tesfatsion (2006). "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," ch. 16, Handbook of Computational Economics, v. 2, [pp. 831-880] sect. 5. Abstract and pre-pub PDF.
• Kenneth L. Judd (2006). "Computationally Intensive Analyses in Economics," Handbook of Computational Economics, v. 2, ch. 17, pp. 881- 893. Pre-pub PDF.
• Leigh Tesfatsion and Kenneth L. Judd, ed. (2006). Handbook of Computational Economics, v. 2. Description Archived 6 March 2012 at the Wayback Machine & and chapter-preview links.
^ ^a ^b B. Arthur, J. Holland, B. LeBaron, R. Palmer, P. Taylor (1997), 'Asset pricing under endogenous expectations in an artificial stock market,' in The Economy as an Evolving Complex System II, B. Arthur, S. Durlauf, and D. Lane, eds., Addison Wesley.
^ Robert Axelrod (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Princeton. Description, contents, and preview.
^ Tomas B. Klosa and Bart Nooteboom, 2001. "Agent-based Computational Transaction Cost Economics," Journal of Economic Dynamics and Control 25(3–4), pp. 503–52. Abstract.
^ • Roberto Leombruni and Matteo Richiardi, ed. (2004), Industry and Labor Dynamics: The Agent-Based Computational Economics Approach. World Scientific Publishing ISBN 981-256-100-5. Description Archived 27 July 2010 at the Wayback Machine and chapter-preview links.
• Joshua M. Epstein (2006). "Growing Adaptive Organizations: An Agent-Based Computational Approach," in Generative Social Science: Studies in Agent-Based Computational Modeling, pp. 309- 344. Description Archived 26 January 2012 at the Wayback Machine and abstract.
^ Robert Axtell (2005). "The Complexity of Exchange," Economic Journal, 115(504, Features), pp. F193-F210.
^ • The New Palgrave Dictionary of Economics (2008), 2nd Edition:
     Roger B. Myerson "mechanism design." Abstract.
     _____. "revelation principle." Abstract.
     Tuomas Sandholm. "computing in mechanism design." Abstract.
   • Noam Nisan and Amir Ronen (2001). "Algorithmic Mechanism Design," Games and Economic Behavior, 35(1-2), pp. 166–196.
   • Noam Nisan et al., ed. (2007). Algorithmic Game Theory, Cambridge University Press. Description Archived 5 May 2012 at the Wayback Machine.
^ Tuomas W. Sandholm and Victor R. Lesser (2001). "Leveled Commitment Contracts and Strategic Breach," Games and Economic Behavior, 35(1-2), pp. 212-270.
^ • David Colander, Peter Howitt, Alan Kirman, Axel Leijonhufvud, and Perry Mehrling, 2008. "Beyond DSGE Models: Toward an Empirically Based Macroeconomics," American Economic Review, 98(2), pp. 236-240. Pre-pub PDF.
• Thomas J. Sargent (1994). Bounded Rationality in Macroeconomics, Oxford. Description and chapter-preview 1st-page links.
• M. Oeffner (2009). 'Agent-based Keynesian Macroeconomics'. PhD thesis, Faculty of Economics, University of Würzburg.
^ A. F. Cottrell, P. Cockshott, G. J. Michaelson, I. P. Wright, V. Yakovenko (2009), Classical Econophysics. Routledge, ISBN 978-0-415-47848-9.
^ Leigh Tesfatsion (2006), "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," ch. 16, Handbook of Computational Economics, v. 2, part 2, ACE study of economic system. Abstract and pre-pub PDF.
^ Summary of methods Archived 26 May 2007 at the Wayback Machine: Department of Economics, Politics and Public Administration, Aalborg University, Denmark website.
^ Vernon L. Smith, 2008. "experimental economics," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
^ Bektas, A., Piana, V. & Schuman, R. A meso-level empirical validation approach for agent-based computational economic models drawing on micro-data: a use case with a mobility mode-choice model. SN Bus Econ 1, 80 (2021). https://doi.org/10.1007/s43546-021-00083-4
^ Giorgio Fagiolo, Alessio Moneta, and Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," Computational Economics, 30, pp. 195–226.
^ Society for Computational Economics website.
^ W. Brock and C. Hommes (1997), 'A rational route to randomness.' Econometrica 65 (5), pp. 1059-1095.
^ C. Hommes (2008), 'Interacting agents in finance,' in The New Palgrave Dictionary of Economics.
^ Brock, W.; Hommes, C.; Wagener, F. (2009). "More hedging instruments may destabilize markets" (PDF). Journal of Economic Dynamics and Control. 33 (11): 1912–1928. doi:10.1016/j.jedc.2009.05.004.
^ M. Buchanan (2009), 'Meltdown modelling. Could agent-based computer models prevent another financial crisis?.' Nature, Vol. 460, No. 7256. (5 August 2009), pp. 680-682.
^ J.D. Farmer, D. Foley (2009), 'The economy needs agent-based modelling.' Nature, Vol. 460, No. 7256. (5 August 2009), pp. 685-686.
^ M. Holcombe, S. Coakley, M.Kiran, S. Chin, C. Greenough, D.Worth, S.Cincotti, M.Raberto, A. Teglio, C. Deissenberg, S. van der Hoog, H. Dawid, S. Gemkow, P. Harting, M. Neugart. Large-scale Modeling of Economic Systems, Complex Systems, 22(2), 175-191, 2013

[1] • W. Brian Arthur, 1994. "Inductive Reasoning and Bounded Rationality," American Economic Review, 84(2), pp. 406-411 Archived 21 May 2013 at the Wayback Machine.
• Leigh Tesfatsion, 2003. "Agent-based Computational Economics: Modeling Economies as Complex Adaptive Systems," Information Sciences, 149(4), pp. 262-268 Archived 26 April 2012 at the Wayback Machine.

[2] Scott E. Page (2008). "agent-based models," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.

[3] Richard S. Sutton and Andrew G. Barto, Reinforcement Learning: An Introduction, The MIT Press, Cambridge, MA, 1998 [1] Archived 4 September 2009 at the Wayback Machine

[4] • John H. Holland and John H. Miller (1991). "Artificial Adaptive Agents in Economic Theory," American Economic Review, 81(2), pp. 365-370 Archived 5 January 2011 at the Wayback Machine p. 366.
• Thomas C. Schelling (1978 [2006]). Micromotives and Macrobehavior, Norton. Description Archived 2 November 2017 at the Wayback Machine, preview.
• Thomas J. Sargent, 1994. Bounded Rationality in Macroeconomics, Oxford. Description and chapter-preview 1st-page links.

[5] • Kenneth L. Judd, 2006. "Computationally Intensive Analyses in Economics," Handbook of Computational Economics, v. 2, ch. 17, Introduction, p. 883. [Pp. 881- 893. Pre-pub PDF.
• _____, 1998. Numerical Methods in Economics, MIT Press. Links to description Archived 11 February 2012 at the Wayback Machine and chapter previews.

[6] • Leigh Tesfatsion (2002). "Agent-Based Computational Economics: Growing Economies from the Bottom Up," Artificial Life, 8(1), pp.55-82. Abstract and pre-pub PDF Archived 14 May 2013 at the Wayback Machine.
• _____ (1997). "How Economists Can Get Alife," in W. B. Arthur, S. Durlauf, and D. Lane, eds., The Economy as an Evolving Complex System, II, pp. 533-564. Addison-Wesley. Pre-pub PDF Archived 15 April 2012 at the Wayback Machine.

[COMP&GT-7] • Joseph Y. Halpern (2008). "computer science and game theory," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.
• Yoav Shoham (2008). "Computer Science and Game Theory," Communications of the ACM, 51(8), pp. 75-79 Archived 26 April 2012 at the Wayback Machine.
• Alvin E. Roth (2002). "The Economist as Engineer: Game Theory, Experimentation, and Computation as Tools for Design Economics," Econometrica, 70(4), pp. 1341–1378.

[8] Tesfatsion, Leigh (2006), "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," ch. 16, Handbook of Computational Economics, v. 2, part 2, ACE study of economic system. Abstract and pre-pub PDF.

[9] • Leigh Tesfatsion (2006). "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," ch. 16, Handbook of Computational Economics, v. 2, [pp. 831-880] sect. 5. Abstract and pre-pub PDF.
• Kenneth L. Judd (2006). "Computationally Intensive Analyses in Economics," Handbook of Computational Economics, v. 2, ch. 17, pp. 881- 893. Pre-pub PDF.
• Leigh Tesfatsion and Kenneth L. Judd, ed. (2006). Handbook of Computational Economics, v. 2. Description Archived 6 March 2012 at the Wayback Machine & and chapter-preview links.

[arthuretal-10] B. Arthur, J. Holland, B. LeBaron, R. Palmer, P. Taylor (1997), 'Asset pricing under endogenous expectations in an artificial stock market,' in The Economy as an Evolving Complex System II, B. Arthur, S. Durlauf, and D. Lane, eds., Addison Wesley.

[11] Robert Axelrod (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Princeton. Description, contents, and preview.

[12] Tomas B. Klosa and Bart Nooteboom, 2001. "Agent-based Computational Transaction Cost Economics," Journal of Economic Dynamics and Control 25(3–4), pp. 503–52. Abstract.

[13] • Roberto Leombruni and Matteo Richiardi, ed. (2004), Industry and Labor Dynamics: The Agent-Based Computational Economics Approach. World Scientific Publishing ISBN 981-256-100-5. Description Archived 27 July 2010 at the Wayback Machine and chapter-preview links.
• Joshua M. Epstein (2006). "Growing Adaptive Organizations: An Agent-Based Computational Approach," in Generative Social Science: Studies in Agent-Based Computational Modeling, pp. 309- 344. Description Archived 26 January 2012 at the Wayback Machine and abstract.

[14] Robert Axtell (2005). "The Complexity of Exchange," Economic Journal, 115(504, Features), pp. F193-F210.

[15] • The New Palgrave Dictionary of Economics (2008), 2nd Edition:
Roger B. Myerson "mechanism design." Abstract.
_____. "revelation principle." Abstract.
Tuomas Sandholm. "computing in mechanism design." Abstract.
• Noam Nisan and Amir Ronen (2001). "Algorithmic Mechanism Design," Games and Economic Behavior, 35(1-2), pp. 166–196.
• Noam Nisan et al., ed. (2007). Algorithmic Game Theory, Cambridge University Press. Description Archived 5 May 2012 at the Wayback Machine.

[16] Tuomas W. Sandholm and Victor R. Lesser (2001). "Leveled Commitment Contracts and Strategic Breach," Games and Economic Behavior, 35(1-2), pp. 212-270.

[17] • David Colander, Peter Howitt, Alan Kirman, Axel Leijonhufvud, and Perry Mehrling, 2008. "Beyond DSGE Models: Toward an Empirically Based Macroeconomics," American Economic Review, 98(2), pp. 236-240. Pre-pub PDF.
• Thomas J. Sargent (1994). Bounded Rationality in Macroeconomics, Oxford. Description and chapter-preview 1st-page links.
• M. Oeffner (2009). 'Agent-based Keynesian Macroeconomics'. PhD thesis, Faculty of Economics, University of Würzburg.

[18] A. F. Cottrell, P. Cockshott, G. J. Michaelson, I. P. Wright, V. Yakovenko (2009), Classical Econophysics. Routledge, ISBN 978-0-415-47848-9.

[19] Leigh Tesfatsion (2006), "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," ch. 16, Handbook of Computational Economics, v. 2, part 2, ACE study of economic system. Abstract and pre-pub PDF.

[20] Summary of methods Archived 26 May 2007 at the Wayback Machine: Department of Economics, Politics and Public Administration, Aalborg University, Denmark website.

[21] Vernon L. Smith, 2008. "experimental economics," The New Palgrave Dictionary of Economics, 2nd Edition. Abstract.

[22] Bektas, A., Piana, V. & Schuman, R. A meso-level empirical validation approach for agent-based computational economic models drawing on micro-data: a use case with a mobility mode-choice model. SN Bus Econ 1, 80 (2021). https://doi.org/10.1007/s43546-021-00083-4

[23] Giorgio Fagiolo, Alessio Moneta, and Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," Computational Economics, 30, pp. 195–226.

[24] Society for Computational Economics website.

[25] W. Brock and C. Hommes (1997), 'A rational route to randomness.' Econometrica 65 (5), pp. 1059-1095.

[26] C. Hommes (2008), 'Interacting agents in finance,' in The New Palgrave Dictionary of Economics.

[27] Brock, W.; Hommes, C.; Wagener, F. (2009). "More hedging instruments may destabilize markets" (PDF). Journal of Economic Dynamics and Control. 33 (11): 1912–1928. doi:10.1016/j.jedc.2009.05.004.

[28] M. Buchanan (2009), 'Meltdown modelling. Could agent-based computer models prevent another financial crisis?.' Nature, Vol. 460, No. 7256. (5 August 2009), pp. 680-682.

[29] J.D. Farmer, D. Foley (2009), 'The economy needs agent-based modelling.' Nature, Vol. 460, No. 7256. (5 August 2009), pp. 685-686.

[30] M. Holcombe, S. Coakley, M.Kiran, S. Chin, C. Greenough, D.Worth, S.Cincotti, M.Raberto, A. Teglio, C. Deissenberg, S. van der Hoog, H. Dawid, S. Gemkow, P. Harting, M. Neugart. Large-scale Modeling of Economic Systems, Complex Systems, 22(2), 175-191, 2013

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+{{Use dmy dates|date=February 2020}}
-'''Agent-based computational economics (ACE)''' is the area of [[computational economics]] that studies economic processes, including whole [[economy|economies]], as [[dynamic system]]s of interacting [[Agent (economics)|agents]]. As such, it falls in the [[paradigm]] of [[complex adaptive system]]s.<ref>• [[W. Brian Arthur]], 1994. "Inductive Reasoning and Bounded Rationality," ''American Economic Review'', 84(2), pp. [http://www-personal.umich.edu/~samoore/bit885f2011/arthur-inductive.pdf 406-411].<br/>&nbsp;&nbsp; • [[Leigh Tesfatsion]], 2003. "Agent-based Computational Economics: Modeling Economies as Complex Adaptive Systems," ''Information Sciences'', 149(4), pp. [http://copper.math.buffalo.edu/urgewiki/uploads/Literature/Tesfatsion2002.pdf 262-268].</ref> In  corresponding [[agent-based model]]s, the "[[agent (economics)|agents]]" are "computational objects modeled as interacting according to rules" over space and time, not real people. The rules are formulated to model behavior and social interactions based on incentives and information.<ref>Scott E. Page (2008). "agent-based models," ''[[The New Palgrave Dictionary of Economics]]'', 2nd Edition. [http://www.dictionaryofeconomics.com/article?id=pde2008_A000218&edition=current&q=agent-based%20computational%20modeling&topicid=&result_number=1 Abstract].</ref> Such rules could also be the result of optimization, realized through use of AI methods (such as [[Q-learning]] and other reinforcement learning techniques)<ref>Richard S. Sutton and Andrew G. Barto, Reinforcement Learning: An Introduction, The MIT Press, Cambridge, MA, 1998 [http://www.cs.ualberta.ca/~sutton/book/ebook/the-book.html]</ref>
+{{Multi-agent system}}
+'''Agent-based computational economics''' ('''ACE''') is the area of [[computational economics]] that studies economic processes, including whole [[economy|economies]], as [[dynamic system]]s of interacting [[Agent (economics)|agents]]. As such, it falls in the [[paradigm]] of [[complex adaptive system]]s.<ref>• [[W. Brian Arthur]], 1994. "[https://ocw.tudelft.nl/wp-content/uploads/ElFarolArtur1994.pdf Inductive Reasoning and Bounded Rationality]," ''American Economic Review'', 84(2), pp. [http://www-personal.umich.edu/~samoore/bit885f2011/arthur-inductive.pdf 406-411] {{Webarchive|url=https://web.archive.org/web/20130521145936/http://www-personal.umich.edu/~samoore/bit885f2011/arthur-inductive.pdf |date=21 May 2013 }}.<br/>&nbsp;&nbsp; • [[Leigh Tesfatsion]], 2003. "Agent-based Computational Economics: Modeling Economies as Complex Adaptive Systems," ''Information Sciences'', 149(4), pp. [http://copper.math.buffalo.edu/urgewiki/uploads/Literature/Tesfatsion2002.pdf 262-268] {{webarchive|url=https://web.archive.org/web/20120426000037/http://copper.math.buffalo.edu/urgewiki/uploads/Literature/Tesfatsion2002.pdf |date=26 April 2012 }}.</ref> In corresponding [[agent-based model]]s, the "[[agent (economics)|agents]]" are "computational objects modeled as interacting according to rules" over space and time, not real people. The rules are formulated to model behavior and social interactions based on incentives and information.<ref>Scott E. Page (2008). "agent-based models," ''[[The New Palgrave Dictionary of Economics]]'', 2nd Edition. [http://www.dictionaryofeconomics.com/article?id=pde2008_A000218&edition=current&q=agent-based%20computational%20modeling&topicid=&result_number=1 Abstract].</ref> Such rules could also be the result of optimization, realized through use of AI methods (such as [[Q-learning]] and other reinforcement learning techniques).<ref>Richard S. Sutton and Andrew G. Barto, Reinforcement Learning: An Introduction, The MIT Press, Cambridge, MA, 1998 [http://www.cs.ualberta.ca/~sutton/book/ebook/the-book.html] {{Webarchive|url=https://web.archive.org/web/20090904194934/http://www.cs.ualberta.ca/~sutton/book/ebook/the-book.html |date=4 September 2009 }}</ref>
-The theoretical assumption of [[mathematical optimization]] by agents in [[equilibrium (economics)|equilibrium]] is replaced by the less restrictive postulate of agents with [[bounded rationality]] ''adapting'' to market forces.<ref>• [[John H. Holland]] and John H. Miller (1991). "Artificial Adaptive Agents in Economic Theory," ''American Economic Review'', 81(2),  pp. [http://www.santafe.edu/media/workingpapers/91-05-025.pdf  365-370] p. 366.<br/>&nbsp;&nbsp; • [[Thomas C. Schelling]] (1978 [2006]).  ''Micromotives and Macrobehavior'', Norton. [http://books.wwnorton.com/books/978-0-393-32946-9/ Description],  [http://books.google.com/books?id=DenWKRgqzWMC&printsec=find&pg=PA1=#v=onepage&q&f=false preview].<br/>&nbsp;&nbsp; •
+The theoretical assumption of [[mathematical optimization]] by agents in [[equilibrium (economics)|equilibrium]] is replaced by the less restrictive postulate of agents with [[bounded rationality]] ''adapting'' to market forces.<ref>• [[John H. Holland]] and John H. Miller (1991). "Artificial Adaptive Agents in Economic Theory," ''American Economic Review'', 81(2), pp. [http://www.santafe.edu/media/workingpapers/91-05-025.pdf  365-370] {{Webarchive|url=https://web.archive.org/web/20110105015853/http://www.santafe.edu/media/workingpapers/91-05-025.pdf |date=5 January 2011 }} p. 366.<br/>&nbsp;&nbsp; • [[Thomas C. Schelling]] (1978 [2006]).  ''Micromotives and Macrobehavior'', Norton. [http://books.wwnorton.com/books/978-0-393-32946-9/ Description] {{Webarchive|url=https://web.archive.org/web/20171102093240/http://books.wwnorton.com/books/978-0-393-32946-9/ |date=2 November 2017 }},  [https://books.google.com/books?id=DenWKRgqzWMC&pg=PA1= preview].<br/>&nbsp;&nbsp; •
-[[Thomas J. Sargent]], 1994. ''Bounded Rationality in Macroeconomics'', Oxford. [http://www.oup.com/us/catalog/general/subject/Economics/MacroeconomicTheory/?view=usa&ci=9780198288695 Description] and chapter-preview 1st-page [http://www.questia.com/library/book/bounded-rationality-in-macroeconomics-thomas-j-sargent-by-thomas-j-sargent.jsp links.]</ref> ACE models apply [[numerical methods]] of analysis to [[Computer simulation|computer-based simulations]] of complex dynamic problems for which more conventional methods, such as theorem formulation, may not find ready use.<ref>• Kenneth L. Judd, 2006. "Computationally Intensive Analyses in Economics," ''Handbook of Computational Economics'', v. 2, ch. 17, Introduction, p. 883. [Pp. [http://books.google.com/books?hl=en&lr=&id=6ITfRkNmKQcC&oi=fnd&pg=PA881&ots=2j0cCBB5S6&sig=a1DlAKMWcxFQZwSkGVVp2zlHIb8#v=onepage&q&f=false 881-] 893. Pre-pub [http://www2.econ.iastate.edu/tesfatsi/Judd.finalrev.pdf PDF].
+[[Thomas J. Sargent]], 1994. ''Bounded Rationality in Macroeconomics'', Oxford. [http://www.oup.com/us/catalog/general/subject/Economics/MacroeconomicTheory/?view=usa&ci=9780198288695 Description] and chapter-preview 1st-page [https://www.questia.com/library/book/bounded-rationality-in-macroeconomics-thomas-j-sargent-by-thomas-j-sargent.jsp links.]</ref> ACE models apply [[numerical methods]] of analysis to [[Computer simulation|computer-based simulations]] of complex dynamic problems for which more conventional methods, such as theorem formulation, may not find ready use.<ref>• Kenneth L. Judd, 2006. "Computationally Intensive Analyses in Economics," ''Handbook of Computational Economics'', v. 2, ch. 17, Introduction, p. 883. [Pp. [https://books.google.com/books?id=6ITfRkNmKQcC&pg=PA881 881-] 893. Pre-pub [https://www2.econ.iastate.edu/tesfatsi/Judd.finalrev.pdf PDF].
-<br/>&nbsp;&nbsp; •  _____, 1998. ''Numerical Methods in Economics'', MIT Press. Links to [http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=3257 description] and [http://books.google.com/books?id=9Wxk_z9HskAC&pg=PR7&source=gbs_toc_r&cad=3#v=onepage&q&f=false chapter previews].</ref> Starting from initial conditions specified by the modeler, the computational economy evolves over time as its constituent agents repeatedly interact with each other, including learning from interactions. In these respects, ACE has been characterized as a bottom-up culture-dish approach to the study of [[economic systems]].<ref>• Leigh Tesfatsion (2002). "Agent-Based Computational Economics: Growing Economies from the Bottom Up," ''Artificial Life'', 8(1), pp.55-82. [http://www.mitpressjournals.org/doi/abs/10.1162/106454602753694765 Abstract] and pre-pub [http://www.econ.brown.edu/fac/Peter_Howitt/SummerSchool/Agent.pdf  PDF].<br/>&nbsp;&nbsp; • _____ (1997). "How Economists Can Get Alife," in W. B. Arthur, S. Durlauf, and D. Lane, eds., ''The Economy as an Evolving Complex System, II'',  pp. 533-564. Addison-Wesley. Pre-pub [http://ageconsearch.umn.edu/bitstream/18196/1/er37.pdf PDF].</ref>
+<br/>&nbsp;&nbsp; •  _____, 1998. ''Numerical Methods in Economics'', MIT Press. Links to [http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=3257 description] {{webarchive|url=https://web.archive.org/web/20120211061602/http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=3257 |date=11 February 2012 }} and [https://books.google.com/books?id=9Wxk_z9HskAC&pg=PR7 chapter previews].</ref> Starting from initial conditions specified by the modeler, the computational economy evolves over time as its constituent agents repeatedly interact with each other, including learning from interactions. In these respects, ACE has been characterized as a bottom-up culture-dish approach to the study of [[economic systems]].<ref>• Leigh Tesfatsion (2002). "Agent-Based Computational Economics: Growing Economies from the Bottom Up," ''Artificial Life'', 8(1), pp.55-82. [http://www.mitpressjournals.org/doi/abs/10.1162/106454602753694765 Abstract] and pre-pub [http://www.econ.brown.edu/fac/Peter_Howitt/SummerSchool/Agent.pdf  PDF] {{webarchive|url=https://web.archive.org/web/20130514143904/http://www.econ.brown.edu/fac/Peter_Howitt/SummerSchool/Agent.pdf |date=14 May 2013 }}.<br/>&nbsp;&nbsp; • _____ (1997). "How Economists Can Get Alife," in W. B. Arthur, S. Durlauf, and D. Lane, eds., ''The Economy as an Evolving Complex System, II'', pp. 533-564. Addison-Wesley. Pre-pub [http://ageconsearch.umn.edu/bitstream/18196/1/er37.pdf PDF] {{Webarchive|url=https://web.archive.org/web/20120415135342/http://ageconsearch.umn.edu/bitstream/18196/1/er37.pdf |date=15 April 2012 }}.</ref>
-ACE has a similarity to, and overlap with, [[game theory]] as an agent-based method for modeling social interactions.<ref name="COMP&GT">• [[Joseph Y. Halpern]] (2008). "computer science and game theory," ''The New Palgrave Dictionary of Economics'', 2nd Edition.  [http://www.dictionaryofeconomics.com/article?id=pde2008_C000566&edition=current&q=&topicid=&result_number=1 Abstract].<br/>&nbsp;&nbsp; • Yoav Shoham (2008). "Computer Science and Game Theory," ''Communications of the ACM'',  51(8), pp.
+ACE has a similarity to, and overlap with, [[game theory]] as an agent-based method for modeling social interactions.<ref name="COMP&GT">• [[Joseph Y. Halpern]] (2008). "computer science and game theory," ''The New Palgrave Dictionary of Economics'', 2nd Edition.  [http://www.dictionaryofeconomics.com/article?id=pde2008_C000566&edition=current&q=&topicid=&result_number=1 Abstract].<br/>&nbsp;&nbsp; • Yoav Shoham (2008). "Computer Science and Game Theory," ''Communications of the ACM'', 51(8), pp.
-[http://www.robotics.stanford.edu/~shoham/www%20papers/CSGT-CACM-Shoham.pdf 75-79].<br/>&nbsp;&nbsp; • [[Alvin E. Roth]] (2002). "The Economist as Engineer: Game Theory, Experimentation, and Computation as Tools for Design Economics," ''Econometrica'', 70(4), pp. [http://kuznets.fas.harvard.edu/~aroth/papers/engineer.pdf 1341–1378].</ref> But practitioners have also noted differences from standard methods, for example in ACE events modeled being driven solely by initial conditions, whether or not equilibria exist or are computationally tractable, and in the modeling facilitation of agent autonomy and learning.<ref>Tesfatsion, Leigh (2006), "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," ch. 16, ''Handbook of Computational Economics'', v. 2, part 2, ACE study of economic system. [http://www.sciencedirect.com/science/article/pii/S1574002105020162 Abstract] and pre-pub [http://econ2.econ.iastate.edu/tesfatsi/hbintlt.pdf PDF].</ref>
+[http://www.robotics.stanford.edu/~shoham/www%20papers/CSGT-CACM-Shoham.pdf 75-79] {{Webarchive|url=https://web.archive.org/web/20120426005917/http://www.robotics.stanford.edu/~shoham/www%20papers/CSGT-CACM-Shoham.pdf |date=26 April 2012 }}.<br/>&nbsp;&nbsp; • [[Alvin E. Roth]] (2002). "The Economist as Engineer: Game Theory, Experimentation, and Computation as Tools for Design Economics," ''Econometrica'', 70(4), pp. [https://web.archive.org/web/20040414102216/http://kuznets.fas.harvard.edu/~aroth/papers/engineer.pdf 1341–1378].</ref> But practitioners have also noted differences from standard methods, for example in ACE events modeled being driven solely by initial conditions, whether or not equilibria exist or are computationally tractable, and in the modeling facilitation of agent autonomy and learning.<ref>Tesfatsion, Leigh (2006), "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," ch. 16, ''Handbook of Computational Economics'', v. 2, part 2, ACE study of economic system. [http://www.sciencedirect.com/science/article/pii/S1574002105020162 Abstract] and pre-pub [http://econ2.econ.iastate.edu/tesfatsi/hbintlt.pdf PDF].</ref>
-The method has benefited from continuing improvements in modeling techniques of [[computer science]] and increased computer capabilities.  The ultimate scientific objective of the method is to "test theoretical findings against real-world data in ways that permit empirically supported theories to cumulate over time, with each researcher’s work building appropriately on the work that has gone before."<ref>• Leigh Tesfatsion (2006). "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," ch. 16, ''Handbook of Computational Economics'', v. 2, [pp. 831-880] sect. 5. [http://www.sciencedirect.com/science/article/pii/S1574002105020162 Abstract] and pre-pub [http://econ2.econ.iastate.edu/tesfatsi/hbintlt.pdf PDF].<br/>&nbsp;&nbsp; • [[Kenneth L. Judd]] (2006). "Computationally Intensive Analyses in Economics," ''Handbook of Computational Economics'', v. 2, ch. 17, pp. [http://books.google.com/books?hl=en&lr=&id=6ITfRkNmKQcC&oi=fnd&pg=PA881&ots=2j0cCBB5S6&sig=a1DlAKMWcxFQZwSkGVVp2zlHIb8#v=onepage&q&f=false 881-] 893. Pre-pub [http://www2.econ.iastate.edu/tesfatsi/Judd.finalrev.pdf PDF].<br/>&nbsp;&nbsp; • Leigh Tesfatsion and Kenneth L. Judd, ed. (2006). ''Handbook of Computational Economics'', v. 2. [http://www.elsevier.com/wps/find/bookdescription.cws_home/660847/description#description Description] & and chapter-preview
+The method has benefited from continuing improvements in modeling techniques of [[computer science]] and increased computer capabilities.  The ultimate scientific objective of the method is to "test theoretical findings against real-world data in ways that permit empirically supported theories to cumulate over time, with each researcher’s work building appropriately on the work that has gone before."<ref>• Leigh Tesfatsion (2006). "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," ch. 16, ''Handbook of Computational Economics'', v. 2, [pp. 831-880] sect. 5. [http://www.sciencedirect.com/science/article/pii/S1574002105020162 Abstract] and pre-pub [http://econ2.econ.iastate.edu/tesfatsi/hbintlt.pdf PDF].<br/>&nbsp;&nbsp; • [[Kenneth L. Judd]] (2006). "Computationally Intensive Analyses in Economics," ''Handbook of Computational Economics'', v. 2, ch. 17, pp. [https://books.google.com/books?id=6ITfRkNmKQcC&pg=PA881 881-] 893. Pre-pub [https://www2.econ.iastate.edu/tesfatsi/Judd.finalrev.pdf PDF].<br/>&nbsp;&nbsp; • Leigh Tesfatsion and Kenneth L. Judd, ed. (2006). ''Handbook of Computational Economics'', v. 2. [http://www.elsevier.com/wps/find/bookdescription.cws_home/660847/description#description Description] {{Webarchive|url=https://web.archive.org/web/20120306100156/http://www.elsevier.com/wps/find/bookdescription.cws_home/660847/description#description |date=6 March 2012 }} & and chapter-preview
-[http://www.sciencedirect.com/science?_ob=PublicationURL&_hubEid=1-s2.0-S1574002105X02003&_cid=273377&_pubType=HS&_auth=y&_acct=C000228598&_version=1&_urlVersion=0&_userid=10&md5=e4757b4f65755ed6340a11fee9615200 links.]</ref> The subject has been applied to research areas like [[asset pricing]],<ref name=arthuretal>B. Arthur, J. Holland, B. LeBaron, R. Palmer, P. Taylor (1997), 'Asset pricing under endogenous expectations in an artificial stock market,' in ''The Economy as an Evolving Complex System II'', B. Arthur, S. Durlauf, and D. Lane, eds., Addison Wesley.</ref> [[competition]] and [[collaboration]],<ref>[[Robert Axelrod]] (1997). ''The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration'', Princeton. [http://press.princeton.edu/titles/6144.html Description], [http://press.princeton.edu/titles/6144.html#TOC contents], and [http://books.google.com/books?id=J0dgRGMdjmQC&printsec=find&pg=PR11#v=onepage&q&f=false preview].</ref> [[transaction cost]]s,<ref>Tomas B. Klosa and Bart Nooteboom, 2001. "Agent-based Computational Transaction Cost Economics,"  ''Journal of Economic Dynamics and Control'' 25(3–4), pp. 503–52. [http://www.sciencedirect.com/science/article/pii/S0165188900000348 Abstract.]</ref> [[market structure]] and [[industrial organization]] and dynamics,<ref>• Roberto Leombruni and Matteo Richiardi, ed. (2004), ''Industry  and Labor Dynamics: The Agent-Based Computational Economics Approach.'' World Scientific Publishing ISBN 981-256-100-5. [http://www.worldscibooks.com/economics/5706.html Description] and chapter-preview [http://books.google.com/books?id=P5O7A5D55nQC&printsec=fond&pg=PR5#v=onepage&q&f=false links].<br/>&nbsp;&nbsp; • [[Joshua M. Epstein]] (2006). "Growing Adaptive Organizations: An Agent-Based Computational Approach," in ''Generative Social Science: Studies in Agent-Based Computational Modeling'', pp. 309 [http://books.google.com/books?hl=en&lr=&id=543OS3qdxBYC&oi=fnd&pg=PA326&dq=false#v=onepage&q=false&f=false -] 344. [http://press.princeton.edu/titles/8277.html Description] and [http://www.santafe.edu/research/working-papers/abstract/99895b6465e8b87656612f8e3570b34c/ abstract].</ref> [[welfare economics]],<ref>[[Robert Axtell]] (2005). "The Complexity of Exchange,"  ''Economic Journal'', 115(504, Features), pp. [http://econfaculty.gmu.edu/pboettke/workshop/archives/f05/Axtell.pdf F193-F210].</ref> and [[mechanism design]],<ref>• ''The New Palgrave Dictionary of Economics'' (2008), 2nd Edition: <br/>&nbsp;&nbsp;&nbsp;&nbsp; [[Roger B. Myerson]] "mechanism design." [http://www.dictionaryofeconomics.com/article?id=pde2008_M000132&edition=current&q=mechanism%20design&topicid=&result_number=3 Abstract.]   <br/>&nbsp;&nbsp;&nbsp;&nbsp; _____. "revelation principle." [http://www.dictionaryofeconomics.com/article?id=pde2008_R000137&edition=current&q=moral&topicid=&result_number=1 Abstract.]<br/>&nbsp;&nbsp;&nbsp;&nbsp; Tuomas Sandholm. "computing in mechanism design." [http://www.dictionaryofeconomics.com/article?id=pde2008_C000563&edition=&field=keyword&q=algorithmic%20mechanism%20design&topicid=&result_number=1 Abstract.]<br/>&nbsp;&nbsp; • [[Noam Nisan]] and Amir Ronen (2001). "Algorithmic Mechanism Design," ''Games and Economic Behavior'',  35(1-2), pp. [http://www.cs.cmu.edu/~sandholm/cs15-892F09/Algorithmic%20mechanism%20design.pdf 166–196].<br/>&nbsp;&nbsp; • [[Noam Nisan]] ''et al''., ed. (2007). ''Algorithmic Game Theory'', Cambridge University Press. [http://www.cup.cam.ac.uk/asia/catalogue/catalogue.asp?isbn=9780521872829 Description].</ref> [[Information economics|information and uncertainty]],<ref>Tuomas W. Sandholm and Victor R. Lesser (2001). "Leveled Commitment Contracts and Strategic Breach," ''Games and Economic Behavior'', 35(1-2), pp. [http://www.cs.cmu.edu/afs/.cs.cmu.edu/Web/People/sandholm/leveled.geb.pdf 212-270].</ref> [[macroeconomics]],<ref>• [[David Colander]], [[Peter Howitt]], Alan Kirman, [[Axel Leijonhufvud]], and [[Perry Mehrling]], 2008. "Beyond DSGE Models: Toward an Empirically Based Macroeconomics," ''American Economic Review'', 98(2), pp. [http://www.jstor.org/pss/29730026 236]-240. Pre-pub [http://www.econ.brown.edu/fac/peter_howitt/publication/complex%20macro6.pdf PDF].<br/>&nbsp;&nbsp; • [[Thomas J. Sargent]] (1994). ''Bounded Rationality in Macroeconomics'', Oxford. [http://www.oup.com/us/catalog/general/subject/Economics/MacroeconomicTheory/?view=usa&ci=9780198288695 Description] and chapter-preview 1st-page [http://www.questia.com/library/book/bounded-rationality-in-macroeconomics-thomas-j-sargent-by-thomas-j-sargent.jsp links].<br/>&nbsp;&nbsp; • M. Oeffner (2009). '[http://www.opus-bayern.de/uni-wuerzburg/volltexte/2009/3927/pdf/OeffnerDissohneAnhang.pdf Agent-based Keynesian Macroeconomics]'. PhD thesis, Faculty of Economics, University of Würzburg.</ref> and [[Marxist economics]].<ref>A. F. Cottrell, P. Cockshott, G. J. Michaelson, I. P. Wright, V. Yakovenko
+[http://www.sciencedirect.com/science?_ob=PublicationURL&_hubEid=1-s2.0-S1574002105X02003&_cid=273377&_pubType=HS&_auth=y&_acct=C000228598&_version=1&_urlVersion=0&_userid=10&md5=e4757b4f65755ed6340a11fee9615200 links.]</ref> The subject has been applied to research areas like [[asset pricing]],<ref name=arthuretal>B. Arthur, J. Holland, B. LeBaron, R. Palmer, P. Taylor (1997), 'Asset pricing under endogenous expectations in an artificial stock market,' in ''The Economy as an Evolving Complex System II'', B. Arthur, S. Durlauf, and D. Lane, eds., Addison Wesley.</ref> [[competition]] and [[collaboration]],<ref>[[Robert Axelrod]] (1997). ''The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration'', Princeton. [http://press.princeton.edu/titles/6144.html Description], [http://press.princeton.edu/titles/6144.html#TOC contents], and [https://books.google.com/books?id=J0dgRGMdjmQC&pg=PR11 preview].</ref> [[transaction cost]]s,<ref>Tomas B. Klosa and [[Bart Nooteboom]], 2001. "Agent-based Computational Transaction Cost Economics,"  ''Journal of Economic Dynamics and Control'' 25(3–4), pp. 503–52. [http://www.sciencedirect.com/science/article/pii/S0165188900000348 Abstract.]</ref> [[market structure]] and [[industrial organization]] and dynamics,<ref>• Roberto Leombruni and Matteo Richiardi, ed. (2004), ''Industry  and Labor Dynamics: The Agent-Based Computational Economics Approach.'' World Scientific Publishing {{ISBN|981-256-100-5}}. [http://www.worldscibooks.com/economics/5706.html Description] {{Webarchive|url=https://web.archive.org/web/20100727221149/http://www.worldscibooks.com/economics/5706.html |date=27 July 2010 }} and chapter-preview [https://books.google.com/books?id=P5O7A5D55nQC&pg=PR5 links].<br/>&nbsp;&nbsp; • [[Joshua M. Epstein]] (2006). "Growing Adaptive Organizations: An Agent-Based Computational Approach," in ''Generative Social Science: Studies in Agent-Based Computational Modeling'', pp. [https://books.google.com/books?id=543OS3qdxBYC&pg=PA309 309-] 344. [http://press.princeton.edu/titles/8277.html Description] {{Webarchive|url=https://web.archive.org/web/20120126180655/http://press.princeton.edu/titles/8277.html |date=26 January 2012 }} and [http://www.santafe.edu/research/working-papers/abstract/99895b6465e8b87656612f8e3570b34c/ abstract].</ref> [[welfare economics]],<ref>[[Robert Axtell]] (2005). "The Complexity of Exchange,"  ''Economic Journal'', 115(504, Features), pp. [http://econfaculty.gmu.edu/pboettke/workshop/archives/f05/Axtell.pdf F193-F210].</ref> and [[mechanism design]],<ref>• ''The New Palgrave Dictionary of Economics'' (2008), 2nd Edition: <br/>&nbsp;&nbsp;&nbsp;&nbsp; [[Roger B. Myerson]] "mechanism design." [http://www.dictionaryofeconomics.com/article?id=pde2008_M000132&edition=current&q=mechanism%20design&topicid=&result_number=3 Abstract.]   <br/>&nbsp;&nbsp;&nbsp;&nbsp; _____. "revelation principle." [http://www.dictionaryofeconomics.com/article?id=pde2008_R000137&edition=current&q=moral&topicid=&result_number=1 Abstract.]<br/>&nbsp;&nbsp;&nbsp;&nbsp; Tuomas Sandholm. "computing in mechanism design." [http://www.dictionaryofeconomics.com/article?id=pde2008_C000563&edition=&field=keyword&q=algorithmic%20mechanism%20design&topicid=&result_number=1 Abstract.]<br/>&nbsp;&nbsp; • [[Noam Nisan]] and Amir Ronen (2001). "Algorithmic Mechanism Design," ''Games and Economic Behavior'',  35(1-2), pp. [https://www.cs.cmu.edu/~sandholm/cs15-892F09/Algorithmic%20mechanism%20design.pdf 166–196].<br/>&nbsp;&nbsp; • [[Noam Nisan]] ''et al''., ed. (2007). ''Algorithmic Game Theory'', Cambridge University Press. [http://www.cup.cam.ac.uk/asia/catalogue/catalogue.asp?isbn=9780521872829 Description] {{Webarchive|url=https://web.archive.org/web/20120505140924/http://www.cup.cam.ac.uk/asia/catalogue/catalogue.asp?isbn=9780521872829 |date=5 May 2012 }}.</ref> [[Information economics|information and uncertainty]],<ref>Tuomas W. Sandholm and Victor R. Lesser (2001). "Leveled Commitment Contracts and Strategic Breach," ''Games and Economic Behavior'', 35(1-2), pp. [https://www.cs.cmu.edu/afs/.cs.cmu.edu/Web/People/sandholm/leveled.geb.pdf 212-270].</ref> [[macroeconomics]],<ref>• [[David Colander]], [[Peter Howitt]], Alan Kirman, [[Axel Leijonhufvud]], and [[Perry Mehrling]], 2008. "Beyond DSGE Models: Toward an Empirically Based Macroeconomics," ''American Economic Review'', 98(2), pp. [https://www.jstor.org/pss/29730026 236]-240. Pre-pub [http://www.brown.edu/Departments/Economics/Faculty/Peter_Howitt/publication/complex%20macro6.pdf PDF].<br/>&nbsp;&nbsp; • [[Thomas J. Sargent]] (1994). ''Bounded Rationality in Macroeconomics'', Oxford. [http://www.oup.com/us/catalog/general/subject/Economics/MacroeconomicTheory/?view=usa&ci=9780198288695 Description] and chapter-preview 1st-page [https://www.questia.com/library/book/bounded-rationality-in-macroeconomics-thomas-j-sargent-by-thomas-j-sargent.jsp links].<br/>&nbsp;&nbsp; • M. Oeffner (2009). '[http://www.opus-bayern.de/uni-wuerzburg/volltexte/2009/3927/pdf/OeffnerDissohneAnhang.pdf Agent-based Keynesian Macroeconomics]'. PhD thesis, Faculty of Economics, University of Würzburg.</ref> and [[Marxist economics]].<ref>A. F. Cottrell, P. Cockshott, G. J. Michaelson, I. P. Wright, V. Yakovenko
-(2009), ''Classical Econophysics.'' Routledge, ISBN 978-0-415-47848-9.</ref><ref>Leigh Tesfatsion (2006), "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," ch. 16, ''Handbook of Computational Economics'', v. 2, part 2, ACE study of economic system. [http://www.sciencedirect.com/science/article/pii/S1574002105020162 Abstract] and pre-pub [http://econ2.econ.iastate.edu/tesfatsi/hbintlt.pdf PDF].</ref>
+(2009), ''Classical Econophysics''. Routledge, {{ISBN|978-0-415-47848-9}}.</ref><ref>Leigh Tesfatsion (2006), "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," ch. 16, ''Handbook of Computational Economics'', v. 2, part 2, ACE study of economic system. [http://www.sciencedirect.com/science/article/pii/S1574002105020162 Abstract] and pre-pub [http://econ2.econ.iastate.edu/tesfatsi/hbintlt.pdf PDF].</ref>
 ==Overview==
-The "[[Agent (economics)|agents]]" in ACE models can represent individuals (e.g. people), social groupings (e.g. firms), biological entities (e.g. growing crops), and/or physical systems (e.g. transport systems). The ACE modeler provides the initial configuration of a computational economic system comprising multiple interacting agents. The modeler then steps back to observe the development of the system over time without further intervention. In particular, system events should be driven by agent interactions without external imposition of equilibrium conditions.<ref>[http://www.socsci.aau.dk/ae2006/ Summary of methods]: ''Department of Economics, Politics and Public Administration, Aalborg University, Denmark'' website.</ref> Issues include those common to [[experimental economics]] in general<ref>[[Vernon L. Smith]], 2008. "experimental economics," ''The New Palgrave Dictionary of Economics'', 2nd Edition. [http://www.dictionaryofeconomics.com/article?id=pde2008_E000277&q=experimental%20&topicid=&result_number=2 Abstract].</ref> and development of a common framework for empirical validation and resolving open questions in agent-based modeling.<ref>Giorgio Fagiolo, Alessio Moneta, and Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," ''Computational Economics'', 30, pp. [http://www.springerlink.com/content/t683473172528275/ 195]–226.</ref>
+The "[[Agent (economics)|agents]]" in ACE models can represent individuals (e.g. people), social groupings (e.g. firms), biological entities (e.g. growing crops), and/or physical systems (e.g. transport systems). The ACE modeler provides the initial configuration of a computational economic system comprising multiple interacting agents. The modeler then steps back to observe the development of the system over time without further intervention. In particular, system events should be driven by agent interactions without external imposition of equilibrium conditions.<ref>[http://www.socsci.aau.dk/ae2006/ Summary of methods] {{Webarchive|url=https://web.archive.org/web/20070526105550/http://www.socsci.aau.dk/ae2006/ |date=26 May 2007 }}: ''Department of Economics, Politics and Public Administration, Aalborg University, Denmark'' website.</ref> Issues include those common to [[experimental economics]] in general<ref>[[Vernon L. Smith]], 2008. "experimental economics," ''The New Palgrave Dictionary of Economics'', 2nd Edition. [http://www.dictionaryofeconomics.com/article?id=pde2008_E000277&q=experimental%20&topicid=&result_number=2 Abstract].</ref> and development of a common framework for empirical validation <ref>Bektas, A., Piana, V. & Schuman, R. A meso-level empirical validation approach for agent-based computational economic models drawing on micro-data: a use case with a mobility mode-choice model. SN Bus Econ 1, 80 (2021). https://doi.org/10.1007/s43546-021-00083-4</ref> and resolving open questions in agent-based modeling.<ref>Giorgio Fagiolo, Alessio Moneta, and Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," ''Computational Economics'', 30, pp. [https://doi.org/10.1007%2Fs10614-007-9104-4 195]–226.</ref>
 ACE is an officially designated special interest group (SIG) of the Society for Computational Economics.<ref>[http://comp-econ.org/ Society for Computational Economics] website.</ref> Researchers at the [[Santa Fe Institute]] have contributed to the development of ACE.
 ==Example: finance==
-One area where ACE methodology has frequently been applied is asset pricing. [[W. Brian Arthur]], [[Eric Baum]], [[William A. Brock (economist)|William Brock]], Cars Hommes, and Blake LeBaron, among others, have developed computational models in which many agents choose from a set of possible forecasting strategies in order to predict stock prices, which affects their asset demands and thus affects stock prices. These models assume that agents are more likely to choose forecasting strategies which have recently been successful. The success of any strategy will depend on market conditions and also on the set of strategies that are currently being used. These models frequently find that large booms and busts in asset prices may occur as agents switch across forecasting strategies.<ref name=arthuretal/><ref>W. Brock and C. Hommes (1997), 'A rational route to randomness.' ''Econometrica'' 65 (5), pp. 1059-1095.</ref><ref>C. Hommes (2008), 'Interacting agents in finance,' in ''The New Palgrave Dictionary of Economics''.</ref> More recently, Brock, Hommes, and Wagener (2009) have used a model of this type to argue that the introduction of new hedging instruments may destabilize the market,<ref>W. Brock, C. Hommes, and F. Wagener (2009), 'More hedging instruments may destabilize markets.' CeNDEF Working Paper.</ref> and some papers have suggested that ACE might be a useful methodology for understanding the recent [[financial crisis]].<ref>M. Buchanan (2009), '[http://pagesperso-orange.fr/mark.buchanan/nature_economic_modelling.pdf Meltdown modelling. Could agent-based computer models prevent another financial crisis?].' Nature, Vol. 460, No. 7256. (05 August 2009), pp. 680-682.</ref><ref>J.D. Farmer, D. Foley (2009), 'The economy needs agent-based modelling.' Nature, Vol. 460, No. 7256. (05 August 2009), pp. 685-686.</ref>
+One area where ACE methodology has frequently been applied is asset pricing. [[W. Brian Arthur]], Eric Baum, [[William A. Brock (economist)|William Brock]], Cars Hommes, and Blake LeBaron, among others, have developed computational models in which many agents choose from a set of possible forecasting strategies in order to predict stock prices, which affects their asset demands and thus affects stock prices. These models assume that agents are more likely to choose forecasting strategies which have recently been successful. The success of any strategy will depend on market conditions and also on the set of strategies that are currently being used. These models frequently find that large booms and busts in asset prices may occur as agents switch across forecasting strategies.<ref name=arthuretal/><ref>W. Brock and C. Hommes (1997), 'A rational route to randomness.' ''Econometrica'' 65 (5), pp. 1059-1095.</ref><ref>C. Hommes (2008), 'Interacting agents in finance,' in ''The New Palgrave Dictionary of Economics''.</ref> More recently, Brock, Hommes, and Wagener (2009) have used a model of this type to argue that the introduction of new hedging instruments may destabilize the market,<ref>{{cite journal |first1=W. |last1=Brock |first2=C. |last2=Hommes |first3=F. |last3=Wagener |year=2009 |title=More hedging instruments may destabilize markets |journal=Journal of Economic Dynamics and Control |volume=33 |issue=11 |pages=1912–1928 |doi=10.1016/j.jedc.2009.05.004 |url=http://cendef.uva.nl/binaries/content/assets/subsites/amsterdam-school-of-economics/amsterdam-school-of-economics-research-institute/cendef/working-papers-2006/brohomwag.pdf?1417181713282 }}</ref> and some papers have suggested that ACE might be a useful methodology for understanding the 2008 [[financial crisis]].<ref>M. Buchanan (2009), '[http://pagesperso-orange.fr/mark.buchanan/nature_economic_modelling.pdf Meltdown modelling. Could agent-based computer models prevent another financial crisis?].' Nature, Vol. 460, No. 7256. (5 August 2009), pp. 680-682.</ref><ref>J.D. Farmer, D. Foley (2009), 'The economy needs agent-based modelling.' Nature, Vol. 460, No. 7256. (5 August 2009), pp. 685-686.</ref><ref>M. Holcombe, S. Coakley, M.Kiran, S. Chin, C. Greenough, D.Worth, S.Cincotti, M.Raberto, A. Teglio, C. Deissenberg, S. van der Hoog, H. Dawid, S. Gemkow, P. Harting, M. Neugart. Large-scale Modeling of Economic Systems, Complex Systems, 22(2), 175-191, 2013</ref>
+See also discussion under {{slink|Financial economics#Financial markets}} and [[Financial_economics#Departures_from_rationality|§ Departures from rationality]].
 ==See also==
-* [[ACEGES]]
 * [[Agent-based social simulation]]
+* [[Artificial economics]]
+* [[Artificial financial market]]
 * [[Computational economics]]
 * [[Econophysics]]
@@ Line 32: / Line 36: @@
 {{Reflist}}
-==Further reading==
-*John Duffy (2006), '[http://www.pitt.edu/~jduffy/papers/duffy2006.pdf Agent-based models and human subject experiments].' Ch. 19 of L. Tesfatsion and K.L. Judd, eds., ''Handbook of Computational Economics'', Vol. 2 (Amsterdam: Elsevier, 2006), pp. 949–1011.
-*[[Sheri Markose]], Jasmina Arifovic, and Shyam Sunder (2007), [http://www.sciencedirect.com/science/article/B6V85-4NJP97X-1/2/96092ac2dfab95f0f07a16f67203e605 'Advances in experimental and agent-based modelling: Asset markets, economic networks, computational mechanism design, and evolutionary game dynamics.'] ''[[Journal of Economic Dynamics and Control]]'' 31, pp. 1801–07.
-*Shoham, Yoav, and Kevin Leyton-Brown, "[http://www.masfoundations.org/ Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations]". Cambridge University Press, 2009.
-==External links==
-*[http://www.econ.iastate.edu/tesfatsi/ace.htm Agent Based Computational Economics] - Leigh Tesfatsion's website on ACE at Iowa State University
-*[http://p.seppecher.free.fr/jamel  JAMEL (a Java Agent-based MacroEconomic Laboratory)] - An on-line, interactive agent-based macroeconomic model
-* [http://www.scribd.com/doc/57052045/The-Use-of-Agent-Based-Models-in-Regional-Science-by-Mark-Kimura The Use of Agent-Based Models in Regional Science] - a study on agent-based models to simulate urban agglomeration
-* [http://learning.londonmet.ac.uk/LMBS/aceges/ACEGESApplet/ACEGESApplet.html ACEGES] - An on-line, interactive agent-based model of the global energy system
-*[http://jcat.sourceforge.net/  JCAT] - A scalable and versatile experimental platform for ACE; used as the Server and Agentware for the Trading Agent Competition on Market Design (also known as the CAT Game)
-*[http://www.crisis-economics.eu/ CRISIS] - A European FP7 project building an integrated macro and financial agent-based simulation model to study economic behavior.
-[[Category:Mathematical economics]]
 [[Category:Computational economics]]
 [[Category:Monte Carlo methods in finance]]
+[[Category:Computational fields of study]]
+[[Category:Agent-based model]]