更改

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. 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. Such rules could also be the result of optimization, realized through use of AI methods (such as Q-learning and other reinforcement learning techniques).

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. 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. Such rules could also be the result of optimization, realized through use of AI methods (such as Q-learning and other reinforcement learning techniques).

'''<font color="#ff8000">基于主体的计算经济学 Agent-based Computational Economics (ACE)</font>'''是[[计算经济学]]的一个领域，将整个经济视作不同主体相互作用的动态系统研究经济过程。因此，它属于复杂适应系统'''<font color="#ff8000">范式 Paradigm</font>'''。在相应的'''<font color="#ff8000">智能体基模型 Agent-based Model(ABM)</font>'''中，“主体”指时空中“根据规则建模的交互计算对象”，而非真实的人。这些规则是为了建立基于激励和信息的行为和社会互动模型而制定的。这些规则也可能是优化的结果，通过人工智能方法（如'''<font color="#ff8000">Q学习 Q-learning</font>'''及其他强化学习技术）来实现。

'''<font color="#ff8000">基于主体的计算经济学 Agent-based Computational Economics (ACE)</font>'''是[[计算经济学]]的一个研究领域，将整个经济视作不同主体相互作用的动态系统，研究经济的发展过程。<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>

因此，它属于[[复杂适应系统]]的科学范式。在相应的[[基于主体模型]]中，“主体”指根据特定规则进行交互的计算实体，而非真实的人。其中交互的规则一种对个体行为和社会互动的建模。<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>

这些规则甚至可以通过人工智能方法（如'''<font color="#ff8000">Q学习 Q-learning</font>'''及其他强化学习技术）来获得。<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] {{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&printsec=find&pg=PA1=#v=onepage&q&f=false preview].<br/>&nbsp;&nbsp; •

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] 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.[6] 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.[7]

[[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 [http://www2.econ.iastate.edu/tesfatsi/Judd.finalrev.pdf PDF].

ACE has a similarity to, and overlap with, game theory as an agent-based method for modeling social interactions.[8] 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.[9]

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-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 [http://www2.econ.iastate.edu/tesfatsi/Judd.finalrev.pdf PDF].

ACE 与博弈论时有相似之处和重叠部分，都可以看作以一种研究社会交往的基于主体的建模方法。但实践者也注意到了ACE与标准的博弈论方法的区别，例如，在ACE中，事件仅由初始条件驱动；ACE不在乎计算上是否易于处理；ACE中，主体有自动选择和学习的能力。

托马斯·萨金特，1994年。牛津大学宏观经济学有限理性。[ http://www.oup.com/us/catalog/general/subject/economics/macroeconomictheory/?view=usa&ci=9780198288695说明]和第一章预览页面[ https://www.questia.com/library/book/bounded-rationality-in-macroeconomics-thomas-j-sargent-by-thomas-j-sargent.jsp 链接]。] / 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."[10] The subject has been applied to research areas like asset pricing,[11] competition and collaboration,[12] transaction costs,[13] market structure and industrial organization and dynamics,[14] welfare economics,[15] and mechanism design,[16] information and uncertainty,[17] macroeconomics,[18] and Marxist economics.[19]

。 文献• Kenneth l. Judd，2006。《经济学中的计算密集分析》 ，《计算经济学手册，第2卷，第5页。17，Introduction，p. 883.[ Pp.Https://books.google.com/books?id=6itfrknmkqcc&pg=pa881881-893.预订酒吧[ http://www2.econ.iastate.edu/tesfatsi/judd.finalrev.PDF  PDF ]。

得益于计算机科学建模技术的不断改进和计算机能力的提高，ACE方法也在不断发展，其终极科学目标是“用实际数据来检验理论发现——使得可靠的、有实际经验和数据支撑的理论能不断积累，而研究人员也能在可靠的前人理论基础上做进一步探索。”现在，ACE方法已应用于如资产定价、竞争与合作、'''<font color="#ff8000">交易成本 Transaction Cost</font>'''、市场形式与'''<font color="#ff8000">产业组织  Industrial Organization</font>'''与动态、'''<font color="#ff8000">福利经济学 Welfare Economics</font>'''、'''<font color="#ff8000">机制设计 Mechanism Design</font>'''、信息与不确定性、'''<font color="#ff8000">宏观经济学 Macroeconomics</font>'''和'''<font color="#ff8000">马克思主义政治经济学 Marxist economics</font>'''等研究领域。

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

该方法得益于计算机科学建模技术的不断改进和计算机能力的提高。其最终科学目标是“用实际数据来检验理论发现——以允许经验支持的理论随着时间的推移而累积的方式（每位研究者的工作恰当建立在之前工作的基础之上）。”其现已应用于如资产定价、竞争与合作、'''<font color="#ff8000">交易成本 Transaction Cost</font>'''、市场形式与'''<font color="#ff8000">产业组织  Industrial Organization</font>'''与动态、'''<font color="#ff8000">福利经济学 Welfare Economics</font>'''、'''<font color="#ff8000">机制设计 Mechanism Design</font>'''、信息与不确定性、'''<font color="#ff8000">宏观经济学 Macroeconomics</font>'''和'''<font color="#ff8000">马克思主义政治经济学 Marxist economics</font>'''等研究领域。

==Overview 概述==

==Overview 概述==

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. Issues include those common to experimental economics in general and development of a common framework for empirical validation and resolving open questions in agent-based modeling.

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. Issues include those common to experimental economics in general and development of a common framework for empirical validation and resolving open questions in agent-based modeling.

ACE 模型中的“主体”可以代表个体（如人）、社会群体（如公司）、生物实体（如生长中的庄稼）和/或物理系统（如运输系统）。ACE 模型提供了由多个相互作用的主体组成的计算经济系统的初始配置。然后，建模人员返回来观察系统随着时间的推移而发展的情况，而不需要进一步的干预。注意，系统活动应由主体间的相互作用驱动，而不需要外部强加的平衡条件。研究问题包括'''<font color="#ff8000">实验经济学 Experimental economics</font>'''通用的问题，以及开发用于经验验证的通用框架和解决基于主体的建模中尚未解决的问题。

ACE 模型中的“主体（agent）”可以代表个体（如人）、社会群体（如公司）、生物实体（如生长中的庄稼）和/或物理系统（如运输系统），整个ACE模型就是由多个相互作用的主体组成的计算经济系统。建模者首先为ACE模型设置初始参数。然后，ACE模型就会自行演化，建模人员则观察系统随着时间的推移而演化的情况，不需要做进一步的干预。注意，系统活动应由主体间的相互作用驱动，而不需要外部强加平衡条件。目前来说，ACE面临的研究问题包括所有'''<font color="#ff8000">实验经济学 Experimental economics</font>'''会遇到的普遍问题，以及开发用于验证模型正确性的的通用框架，和其他基于主体的建模中尚未解决的开放问题。

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

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

ACE 是美国计算经济学学会的一个官方指定的特殊利益集团 (SIG) 。[[圣菲研究所 Santa Fe Institute]]的研究人员为 ACE 的发展做出了贡献。

ACE 同时也是是美国计算经济学学会的一个官方特殊兴趣团体 (SIG) 。[[圣塔菲研究所_Santa_Fe_Institute|圣菲研究所]]的研究人员为 ACE 的发展做出了贡献。

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. 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, and some papers have suggested that ACE might be a useful methodology for understanding the recent financial crisis.

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. 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, and some papers have suggested that ACE might be a useful methodology for understanding the recent financial crisis.

ACE 方法已广泛应用的领域之一是资产定价。'''布莱恩·亚瑟 W. Brian Arthur'''，'''埃里克·鲍姆 Eric Baum'''，'''威廉·布洛克 William Brock'''，Cars Hommes，'''布莱克·勒巴朗 Blake LeBaron'''等人已开发出一个计算模型，其中许多主体从一组可能的预测策略中选择以预测股票价格，这影响了他们的资产需求，进而影响股票价格。这些模型假设主体更有可能选择最近成功的预测策略。任何策略的成功取决于市场条件，也取决于目前正在使用的一组策略。这些模型经常表明，随着主体改换预测策略，资产价格可能会出现大起大落。最近，布洛克、Hommes 和'''瓦格纳 Wagener''' （2009）使用了这类模型来论证引入新的对冲工具可能会破坏市场稳定，一些论文提出，ACE 可能是理解最近金融危机的有用方法。

ACE 方法已广泛应用的领域之一是资产定价。'''布莱恩·亚瑟 W. Brian Arthur'''，'''埃里克·鲍姆 Eric Baum'''，'''威廉·布洛克 William Brock'''，Cars Hommes，'''布莱克·勒巴朗 Blake LeBaron'''等人已开发出一个计算模型，其中许多主体从一组可能的预测策略中选择一种或几种以预测股票价格，他们自己的预测结果影响了他们的自己的资产需求，进而影响整体股票价格。这些模型假设每个主体更有可能选择最近前几轮中成功的预测策略。任何策略的成功取决于市场条件，也取决于目前正在被主体们使用的预测策略。这些模型的实验结果经常表明，随着主体改换预测策略，资产价格可能会出现大起大落。最近，布洛克、Hommes 和'''瓦格纳 Wagener''' （2009）使用了这类模型来论证引入新的对冲工具可能会破坏市场稳定，一些论文提出，ACE 可能是理解最近金融危机的有用方法。