“有限理性”的版本间的差异

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（Moved page from wikipedia:en:Bounded rationality (history)）
 
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此词条暂由彩云小译翻译，翻译字数共759，未经人工整理和审校，带来阅读不便，请见谅。
  
 
'''Bounded rationality''' is the idea that [[rationality]] is limited, when individuals make decisions, by the tractability of the decision problem, the cognitive limitations of the mind, and the time available to make the decision. Decision-makers, in this view, act as [[satisficer]]s, seeking a satisfactory solution rather than an optimal one.  
 
'''Bounded rationality''' is the idea that [[rationality]] is limited, when individuals make decisions, by the tractability of the decision problem, the cognitive limitations of the mind, and the time available to make the decision. Decision-makers, in this view, act as [[satisficer]]s, seeking a satisfactory solution rather than an optimal one.  
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Bounded rationality is the idea that rationality is limited, when individuals make decisions, by the tractability of the decision problem, the cognitive limitations of the mind, and the time available to make the decision. Decision-makers, in this view, act as satisficers, seeking a satisfactory solution rather than an optimal one.  
 
Bounded rationality is the idea that rationality is limited, when individuals make decisions, by the tractability of the decision problem, the cognitive limitations of the mind, and the time available to make the decision. Decision-makers, in this view, act as satisficers, seeking a satisfactory solution rather than an optimal one.  
  
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有限理性是这样一种观点，即当个体做出决定时，理性是有限的，受决定问题的可处理性、大脑的认知局限性以及做出决定的可用时间的限制。这种观点认为，决策者作为满足者，寻求一个令人满意的解决方案，而不是一个最佳的解决方案。
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有限理性是这样一种观点，即当个体做出决定时，理性是有限的，受决定问题的可控性、大脑的认知局限性以及做出决定的可用时间的限制。这种观点认为，决策者作为满足者，寻求一个令人满意的解决方案，而不是一个最佳的解决方案。
  
  
  
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[[Herbert A. Simon]] proposed bounded rationality as an alternative basis for the mathematical modeling of [[decision-making]], as used in [[economics]], [[political science]] and related disciplines. It complements "rationality as optimization", which views decision-making as a fully rational process of finding an optimal choice given the information available.<ref name="bounded_rationality_1999">{{cite book|url=https://books.google.com/?id=dVMq5UoYS3YC&dq=%22bounded+rationality%22&printsec=frontcover|first=Gerd|last=Gigerenzer|first2=Reinhard|last2=Selten|title=Bounded Rationality: The Adaptive Toolbox|publisher=MIT Press|year=2002|isbn=978-0-262-57164-7}}</ref> Simon used the analogy of a pair of scissors, where one blade represents "cognitive limitations" of actual humans and the other the "structures of the environment", illustrating how minds compensate for limited resources by exploiting known structural regularity in the environment.<ref name="bounded_rationality_1999" /> Many [[economics]] models assume that people are on average rational, and can in large enough quantities be approximated to act according to their [[preference]]s. The concept of bounded rationality revises this assumption to account for the fact that perfectly rational decisions are often not feasible in practice because of the intractability of natural decision problems and the finite computational resources available for making them.
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[[Herbert A. Simon]] proposed bounded rationality as an alternative basis for the mathematical modeling of [[decision-making]], as used in [[economics]], [[political science]] and related disciplines. It complements "rationality as optimization", which views decision-making as a fully rational process of finding an optimal choice given the information available.<ref name="bounded_rationality_1999">{{cite book|url=https://books.google.com/books?id=dVMq5UoYS3YC&dq=%22bounded+rationality%22&printsec=frontcover|first1=Gerd|last1=Gigerenzer|first2=Reinhard|last2=Selten|title=Bounded Rationality: The Adaptive Toolbox|publisher=MIT Press|year=2002|isbn=978-0-262-57164-7}}</ref> Simon used the analogy of a pair of scissors, where one blade represents "cognitive limitations" of actual humans and the other the "structures of the environment", illustrating how minds compensate for limited resources by exploiting known structural regularity in the environment.<ref name="bounded_rationality_1999" /> Many [[economics]] models assume that people are on average rational, and can in large enough quantities be approximated to act according to their [[preference]]s. With bounded rationality, Simon's goal was "to replace the global rationality of economic man with a kind of rational behavior that is compatible with the access to information and the computational capacities that are actually possessed by organisms, including man, in the kinds of environments in which such organisms exist."<ref>{{Cite journal|last=Simon|first=Herbert A.|date=1955-02-01|title=A Behavioral Model of Rational Choice|url=https://academic.oup.com/qje/article/69/1/99/1919737|journal=The Quarterly Journal of Economics|language=en|volume=69|issue=1|pages=99–118|doi=10.2307/1884852|jstor=1884852|issn=0033-5533}}</ref> In short, the concept of bounded rationality revises notions of "perfect" rationality to account for the fact that perfectly rational decisions are often not feasible in practice because of the intractability of natural decision problems and the finite computational resources available for making them.
  
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Herbert A. Simon proposed bounded rationality as an alternative basis for the mathematical modeling of decision-making, as used in economics, political science and related disciplines. It complements "rationality as optimization", which views decision-making as a fully rational process of finding an optimal choice given the information available. Simon used the analogy of a pair of scissors, where one blade represents "cognitive limitations" of actual humans and the other the "structures of the environment", illustrating how minds compensate for limited resources by exploiting known structural regularity in the environment. Many economics models assume that people are on average rational, and can in large enough quantities be approximated to act according to their preferences. The concept of bounded rationality revises this assumption to account for the fact that perfectly rational decisions are often not feasible in practice because of the intractability of natural decision problems and the finite computational resources available for making them.
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Herbert A. Simon proposed bounded rationality as an alternative basis for the mathematical modeling of decision-making, as used in economics, political science and related disciplines. It complements "rationality as optimization", which views decision-making as a fully rational process of finding an optimal choice given the information available. Many economics models assume that people are on average rational, and can in large enough quantities be approximated to act according to their preferences. With bounded rationality, Simon's goal was "to replace the global rationality of economic man with a kind of rational behavior that is compatible with the access to information and the computational capacities that are actually possessed by organisms, including man, in the kinds of environments in which such organisms exist."
  
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赫伯特·西蒙提议将有限理性作为决策过程数学建模的替代基础，用于经济学、政治学和相关学科。它补充了“理性即优化”的观点，这种观点认为，决策是一个完全理性的过程，找到一个最佳的选择给予信息。西蒙使用了一把剪刀的类比，一把刀片代表实际人类的”认知局限” ，另一把代表”环境的结构” ，说明人类如何通过利用已知的环境结构规律来弥补有限的资源。许多经济学模型假设人们一般都是理性的，并且可以大量地根据他们的偏好来近似地行动。有限理性的概念修正了这个假设，因为由于自然决策问题的棘手性和有限的可用计算资源，完全理性的决策在实践中往往是不可行的。
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赫伯特·西蒙提出有限理性作为决策的数学建模的替代基础，用于经济学、政治学和相关学科。它补充了“理性即优化”的观点，该观点认为，决策是一个完全理性的过程，找到一个最佳的选择给予信息。许多经济学模型假设人们一般都是理性的，并且可以大量地根据他们的偏好来近似地行动。通过有限理性，Simon 的目标是“用一种理性行为来取代经济人的全球理性，这种理性行为与有机体，包括人，在这种有机体存在的环境中实际拥有的信息获取和计算能力是相容的。”
  
  
  
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Some models of [[human behavior]] in the [[social sciences]] assume that [[humans]] can be reasonably approximated or described as "[[rationality|rational]]" entities, as in [[rational choice theory]] or Downs Political Agency Models.<ref name="Olson">Mancur Olson, Jr.  ([1965] 1971). ''The Logic of Collective Action: Public Goods and the Theory of Groups'', 2nd ed. Harvard University Press, [http://www.hup.harvard.edu/catalog.php?isbn=9780674537514 Description], [http://www.hup.harvard.edu/catalog.php?recid=24500&content=toc Table of Contents], and [https://archive.org/details/logicofcollectiv00olso_0/page/5 preview].</ref>  
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The concept of bounded rationality continues to influence (and be debated in) different disciplines, including economics, psychology, law, political science and cognitive science.<ref>{{Cite journal|last1=Chater|first1=Nick|last2=Felin|first2=Teppo|last3=Funder|first3=David C.|last4=Gigerenzer|first4=Gerd|last5=Koenderink|first5=Jan J.|last6=Krueger|first6=Joachim I.|last7=Noble|first7=Denis|last8=Nordli|first8=Samuel A.|last9=Oaksford|first9=Mike|last10=Schwartz|first10=Barry|last11=Stanovich|first11=Keith E.|date=2018-04-01|title=Mind, rationality, and cognition: An interdisciplinary debate|journal=Psychonomic Bulletin & Review|language=en|volume=25|issue=2|pages=793–826|doi=10.3758/s13423-017-1333-5|issn=1531-5320|pmc=5902517|pmid=28744767}}</ref> Some models of [[human behavior]] in the [[social sciences]] assume that [[humans]] can be reasonably approximated or described as "[[rationality|rational]]" entities, as in [[rational choice theory]] or Downs Political Agency Models.<ref name="Olson">Mancur Olson, Jr.  ([1965] 1971). ''The Logic of Collective Action: Public Goods and the Theory of Groups'', 2nd ed. Harvard University Press, [http://www.hup.harvard.edu/catalog.php?isbn=9780674537514 Description], [http://www.hup.harvard.edu/catalog.php?recid=24500&content=toc Table of Contents], and [https://archive.org/details/logicofcollectiv00olso_0/page/5 preview].</ref>
  
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Some models of human behavior in the social sciences assume that humans can be reasonably approximated or described as "rational" entities, as in rational choice theory or Downs Political Agency Models.
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Huw Dixon later argues that it may not be necessary to analyze in detail the process of reasoning underlying bounded rationality.  If we believe that agents will choose an action that gets them "close" to the optimum, then we can use the notion of epsilon-optimization, which means we choose our actions so that the payoff is within epsilon of the optimum. If we define the optimum (best possible) payoff as <math> U^* </math>, then the set of epsilon-optimizing options S(ε) can be defined as all those options s such that:
  
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社会科学中的一些人类行为模型假定人类可以被合理地近似或描述为“理性”实体，如理性选择理论或唐斯政治机构模型。
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后来认为，也许没有必要详细分析有限理性的推理过程。如果我们相信代理人会选择一个让他们“接近”最优的行动，那么我们可以使用 epsilon 优化的概念，这意味着我们选择我们的行动，使得回报在最优的 epsilon 之内。如果我们将最优(最佳可能)收益定义为 < math > u ^ * </math > ，那么 epsilon-optimization 选项集 s (ε)就可以定义为所有这些选项:
  
  
  
 
==Origins==
 
==Origins==
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<math> U(s) \geq U^*-\epsilon</math>.
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[ math ] u (s) geq u ^ *-epsilon.
  
 
The term was coined by [[Herbert A. Simon]]. In ''Models of Man'', Simon points out that most people are only partly rational, and are irrational in the remaining part of their actions. In another work, he states "boundedly rational agents experience limits in formulating and solving complex problems and in processing (receiving, storing, retrieving, transmitting) [[information]]".<ref>[[Oliver E. Williamson]], p.&nbsp;553, citing Simon.</ref> Simon describes a number of dimensions along which "classical" models of rationality can be made somewhat more realistic, while sticking within the vein of fairly rigorous formalization. These include:
 
The term was coined by [[Herbert A. Simon]]. In ''Models of Man'', Simon points out that most people are only partly rational, and are irrational in the remaining part of their actions. In another work, he states "boundedly rational agents experience limits in formulating and solving complex problems and in processing (receiving, storing, retrieving, transmitting) [[information]]".<ref>[[Oliver E. Williamson]], p.&nbsp;553, citing Simon.</ref> Simon describes a number of dimensions along which "classical" models of rationality can be made somewhat more realistic, while sticking within the vein of fairly rigorous formalization. These include:
  
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The term was coined by Herbert A. Simon. In Models of Man, Simon points out that most people are only partly rational, and are irrational in the remaining part of their actions. In another work, he states "boundedly rational agents experience limits in formulating and solving complex problems and in processing (receiving, storing, retrieving, transmitting) information". Simon describes a number of dimensions along which "classical" models of rationality can be made somewhat more realistic, while sticking within the vein of fairly rigorous formalization. These include:
 
  
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这个术语是由赫伯特·西蒙创造的。在《人类模型》一书中，西蒙指出，大多数人只是部分地理性，在他们行为的其余部分是非理性的。在另一部著作中，他指出“有限理性的代理人在制定和解决复杂问题以及处理(接收、存储、检索、传输)信息方面经验有限”。西蒙描述了一些维度，沿着这些维度，“经典”的理性模型可以变得更加现实一些，同时坚持相当严格的形式化的脉络。其中包括:
 
  
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The notion of strict rationality is then a special case (ε=0). The advantage of this approach is that it avoids having to specify in detail the process of reasoning, but rather simply assumes that whatever the process is, it is good enough to get near to the optimum.
  
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严格合理性的概念是一个特例(ε = 0)。这种方法的优点在于，它避免了详细说明推理过程，而是简单地假设无论过程是什么，它都足以接近最优值。
  
 
* limiting the types of [[utility]] functions
 
* limiting the types of [[utility]] functions
  
 
* recognizing the costs of gathering and processing information
 
* recognizing the costs of gathering and processing information
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From a computational point of view, decision procedures can be encoded in algorithms and heuristics. Edward Tsang argues that the effective rationality of an agent is determined by its computational intelligence. Everything else being equal, an agent that has better algorithms and heuristics could make "more rational" (more optimal) decisions than one that has poorer heuristics and algorithms. Tshilidzi Marwala and Evan Hurwitz in their study on bounded rationality observed that advances in technology (e.g. computer processing power because of Moore's law, artificial intelligence and big data analytics) expand the bounds that define the feasible rationality space. Because of this expansion of the bounds of rationality, machine automated decision making makes markets more efficient.
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从计算的角度来看，决策过程可以编码在算法和启发式。曾德昌认为，智能体的有效合理性取决于其计算智能。在其他条件相同的情况下，一个拥有更好的算法和启发式的智能体可以比那些启发式和算法较差的智能体做出“更理性”(更优化)的决策。和 Evan Hurwitz 在他们关于有限理性的研究中观察到技术的进步(例如:。由于摩尔定律、人工智能和大数据分析等因素的影响，计算机处理能力扩展了界定可行理性空间的范围。由于这种理性边界的扩展，机器自动决策使市场更有效率。
  
 
* the possibility of having a "[[vector (geometry)|vector]]" or "multi-valued" utility function
 
* the possibility of having a "[[vector (geometry)|vector]]" or "multi-valued" utility function
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Simon suggests that economic agents use [[heuristics in judgment and decision-making|heuristics]] to make decisions rather than a strict rigid rule of optimization. They do this because of the complexity of the situation.
 
Simon suggests that economic agents use [[heuristics in judgment and decision-making|heuristics]] to make decisions rather than a strict rigid rule of optimization. They do this because of the complexity of the situation.
  
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Simon suggests that economic agents use heuristics to make decisions rather than a strict rigid rule of optimization. They do this because of the complexity of the situation.
 
  
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西蒙认为，经济主体使用启发式而不是一个严格的最优化规则作出决定。他们这样做是因为情况的复杂性。
 
  
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Bounded rationality implies the idea that humans take reasoning shortcuts that may lead to suboptimal decision-making. Behavioral economists engage in mapping the decision shortcuts that agents use in order to help increase the effectiveness of human decision-making. One treatment of this idea comes from Cass Sunstein and Richard Thaler's Nudge. Sunstein and Thaler recommend that choice architectures are modified in light of human agents' bounded rationality. A widely cited proposal from Sunstein and Thaler urges that healthier food be placed at sight level in order to increase the likelihood that a person will opt for that choice instead of a less healthy option. Some critics of Nudge have lodged attacks that modifying choice architectures will lead to people becoming worse decision-makers.
  
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有限理性意味着人类走了一条可能导致次优决策的推理捷径。行为经济学家从事绘制决策捷径，代理人使用，以帮助提高人类决策的有效性。卡斯 · 桑斯坦和理查德 · 塞勒对这一观点的一种论述来自《轻推》。和 Thaler 建议选择的结构应该根据人类代理的有限理性来修改。桑斯坦和泰勒提出的一个被广泛引用的建议是，为了增加人们选择健康食品而不是不健康食品的可能性，应该把健康食品放在视线范围内。一些对 Nudge 持批评态度的人指出，修改选择架构将导致人们成为更糟糕的决策者。
  
 
==Model extensions==
 
==Model extensions==
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As decision-makers have to make decisions about how and when to decide, [[Ariel Rubinstein]] proposed to model bounded rationality by explicitly specifying decision-making procedures.<ref>{{cite book |author=Rubinstein, Ariel |title=Modeling bounded rationality |publisher=MIT Press |year=1997 |url = http://arielrubinstein.tau.ac.il/book-br.html | isbn=9780262681001 }}</ref> This puts the study of decision procedures on the research agenda.
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Bounded rationality was shown to be essential to predict human sociability properties in a particular model by Vernon L. Smith and Michael J. Campbell. There, an agent-based model correctly predicts that agents are averse to resentment and punishment, and that there is an asymmetry between gratitude/reward and resentment/punishment. The purely rational Nash equilibrium is shown to have no predictive power for that model, and the boundedly rational Gibbs equilibrium must be used to predict phenomena outlined in Humanomics.
  
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As decision-makers have to make decisions about how and when to decide, Ariel Rubinstein proposed to model bounded rationality by explicitly specifying decision-making procedures. This puts the study of decision procedures on the research agenda.
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由 Vernon l. Smith 和 Michael j. Campbell 研究表明，在一个特定的模型中，有限理性对于预测人类的社交能力是必不可少的。在这里，个体为本模型预测正确地预测了代理人厌恶怨恨和惩罚，并且在感激/奖励和怨恨/惩罚之间存在着不对称。纯理性的纳什均衡点对于这个模型没有预测能力，有限理性的吉布斯平衡必须用来预测在 Humanomics 概述的现象。
  
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由于决策者必须决定如何以及何时做出决定，阿里埃勒·鲁宾斯坦提议通过明确规定决策程序来建立有限理性的模型。这就把决策程序的研究提上了研究日程。
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As decision-makers have to make decisions about how and when to decide, [[Ariel Rubinstein]] proposed to model bounded rationality by explicitly specifying decision-making procedures.<ref>{{cite book |author=Rubinstein, Ariel |title=Modeling bounded rationality |publisher=MIT Press |year=1997 |url = http://arielrubinstein.tau.ac.il/book-br.html | isbn=9780262681001 }}</ref> This puts the study of decision procedures on the research agenda.
  
  
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[[Gerd Gigerenzer]] opines that decision theorists have not really adhered to Simon's original ideas. Rather, they have considered how decisions may be crippled by limitations to rationality, or have modeled how people might cope with their inability to optimize. Gigerenzer proposes and shows that simple [[heuristic]]s often lead to better decisions than theoretically optimal procedures.<ref name="Olson"/>
 
[[Gerd Gigerenzer]] opines that decision theorists have not really adhered to Simon's original ideas. Rather, they have considered how decisions may be crippled by limitations to rationality, or have modeled how people might cope with their inability to optimize. Gigerenzer proposes and shows that simple [[heuristic]]s often lead to better decisions than theoretically optimal procedures.<ref name="Olson"/>
  
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Gerd Gigerenzer opines that decision theorists have not really adhered to Simon's original ideas. Rather, they have considered how decisions may be crippled by limitations to rationality, or have modeled how people might cope with their inability to optimize. Gigerenzer proposes and shows that simple heuristics often lead to better decisions than theoretically optimal procedures.
 
  
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格尔德 · 吉格伦泽认为，决策理论家并没有真正坚持西蒙的原始观点。相反，他们考虑了决策如何被理性的限制所削弱，或者模拟了人们如何应对他们无法优化的情况。Gigerenzer 提出并证明了简单的启发法往往比理论上的最佳程序导致更好的决策。
 
  
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Recent research has shown that bounded rationality of individuals may influence the topology of the social networks that evolve among them. In particular, Kasthurirathna and Piraveenan have shown that in socio-ecological systems, the drive towards improved rationality on average might be an evolutionary reason for the emergence of scale-free properties. They did this by simulating a number of strategic games on an initially random network with distributed bounded rationality, then re-wiring the network so that the network on average converged towards Nash equilibria, despite the bounded rationality of nodes. They observed that this re-wiring process results in scale-free networks. Since scale-free networks are ubiquitous in social systems, the link between bounded rationality distributions and social structure is an important one in explaining social phenomena.
  
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最近的研究表明，个体的有限理性可能会影响其中进化的社交网络的拓扑结构。特别是，Kasthurirathna 和 Piraveenan 已经表明，在社会生态系统中，平均而言，改善理性的驱动力可能是无尺度特性出现的进化原因。他们通过模拟一个具有分布式有限理性的最初随机网络中的一系列策略游戏，然后重新布线网络，使网络平均收敛到纳什均衡，尽管节点有限理性很大。他们观察到，这种重新布线的过程导致了无标度网络。由于无标度网络在社会系统中无处不在，有限理性分布和社会结构之间的联系是解释社会现象的一个重要因素。
  
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[[Huw Dixon]] later argues that it may not be necessary to analyze in detail the process of reasoning underlying bounded rationality.<ref>{{cite book |chapter=Some Thoughts on Artificial Intelligence and Economic Theory |editor-last=Moss |editor2-last=Rae |title=Artificial Intelligence and Economic Analysis |publisher=Edward Elgar |location= |year=1992 |pages=[https://archive.org/details/artificialintell0000unse_a9c0/page/131 131–154] |doi= |isbn=978-1852786854 |url=https://archive.org/details/artificialintell0000unse_a9c0/page/131 }}</ref>  If we believe that agents will choose an action that gets them "close" to the optimum, then we can use the notion of ''epsilon-optimization'', which means we choose our actions so that the payoff is within epsilon of the optimum. If we define the optimum (best possible) payoff as <math> U^* </math>, then the set of epsilon-optimizing options '''S(ε)''' can be defined as all those options '''s''' such that:
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[[Huw Dixon]] later argues that it may not be necessary to analyze in detail the process of reasoning underlying bounded rationality.<ref>{{cite book |chapter=Some Thoughts on Artificial Intelligence and Economic Theory |editor-last=Moss |editor2-last=Rae |title=Artificial Intelligence and Economic Analysis |publisher=Edward Elgar |location= |year=1992 |pages=[https://archive.org/details/artificialintell0000unse_a9c0/page/131 131–154] |doi= |isbn=978-1852786854 |chapter-url=https://archive.org/details/artificialintell0000unse_a9c0/page/131 }}</ref>  If we believe that agents will choose an action that gets them "close" to the optimum, then we can use the notion of ''epsilon-optimization'', which means we choose our actions so that the payoff is within epsilon of the optimum. If we define the optimum (best possible) payoff as <math> U^* </math>, then the set of epsilon-optimizing options '''S(ε)''' can be defined as all those options '''s''' such that:
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Huw Dixon later argues that it may not be necessary to analyze in detail the process of reasoning underlying bounded rationality.  If we believe that agents will choose an action that gets them "close" to the optimum, then we can use the notion of epsilon-optimization, which means we choose our actions so that the payoff is within epsilon of the optimum. If we define the optimum (best possible) payoff as <math> U^* </math>, then the set of epsilon-optimizing options S(ε) can be defined as all those options s such that:
 
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后来认为，也许没有必要详细分析有限理性的推理过程。如果我们相信代理人会选择一个让他们“接近”最优的行动，那么我们可以使用 epsilon 优化的概念，这意味着我们选择我们的行动，使得回报在最优的 epsilon 之内。如果我们将最优(最佳可能)收益定义为 math u ^ * / math，那么 epsilon-optimization 选项集 s ()可以定义为所有这些选项，如下:
 
  
  
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<math> U(s) \geq U^*-\epsilon</math>.
 
<math> U(s) \geq U^*-\epsilon</math>.
  
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<math> U(s) \geq U^*-\epsilon</math>.
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数学 u (s) geq u ^ *- epsilon / math。
 
  
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The notion of strict rationality is then a special case (ε=0). The advantage of this approach is that it avoids having to specify in detail the process of reasoning, but rather simply assumes that whatever the process is, it is good enough to get near to the optimum.
 
  
 
The notion of strict rationality is then a special case (ε=0). The advantage of this approach is that it avoids having to specify in detail the process of reasoning, but rather simply assumes that whatever the process is, it is good enough to get near to the optimum.
 
The notion of strict rationality is then a special case (ε=0). The advantage of this approach is that it avoids having to specify in detail the process of reasoning, but rather simply assumes that whatever the process is, it is good enough to get near to the optimum.
  
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那么，严格理性的概念就是一个特例(0)。这种方法的优点在于它避免了详细说明推理过程，而是简单地假设无论过程是什么，它都足以接近最优值。
 
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From a computational point of view, decision procedures can be encoded in [[algorithms]] and [[heuristics]]. [[Edward Tsang]] argues that the effective rationality of an agent is determined by its [[computational intelligence]]. Everything else being equal, an agent that has better algorithms and heuristics could make "more rational" (more optimal) decisions than one that has poorer heuristics and algorithms.<ref>{{cite journal |doi=10.1007/s11633-008-0063-6 |author=Tsang, E.P.K. |title=Computational intelligence determines effective rationality |journal= International Journal of Automation and Computing|volume=5 |issue=1 |pages=63–6 |year=2008 }}</ref> [[Tshilidzi Marwala]] and [[Evan Hurwitz]] in their study on bounded rationality observed that advances in technology (e.g. computer processing power because of [[Moore's law]], [[artificial intelligence]] and big data analytics) expand the bounds that define the feasible rationality space. Because of this expansion of the bounds of rationality, machine automated decision making makes markets more efficient.<ref>{{cite book |last1=Marwala |first1= Tshilidzi| last2=Hurwitz |first2= Evan |title=Artificial Intelligence and Economic Theory: Skynet in the Market |year=2017 |publisher=[[Springer Science+Business Media|Springer]] |location=London |isbn=978-3-319-66104-9}}</ref>
 
  
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From a computational point of view, decision procedures can be encoded in algorithms and heuristics. Edward Tsang argues that the effective rationality of an agent is determined by its computational intelligence. Everything else being equal, an agent that has better algorithms and heuristics could make "more rational" (more optimal) decisions than one that has poorer heuristics and algorithms. Tshilidzi Marwala and Evan Hurwitz in their study on bounded rationality observed that advances in technology (e.g. computer processing power because of Moore's law, artificial intelligence and big data analytics) expand the bounds that define the feasible rationality space. Because of this expansion of the bounds of rationality, machine automated decision making makes markets more efficient.
 
  
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从计算的角度来看，决策过程可以编码在算法和启发式。曾荫权认为，智能体的有效合理性取决于其计算智能。在其他条件相同的情况下，一个拥有更好算法和启发式的智能体可以比那些启发式和算法较差的智能体做出“更理性”(更优化)的决策。Tshilidzi Marwala 和 Evan Hurwitz 在他们关于有限理性的研究中观察到技术的进步(例如:。计算机处理能力因为摩尔定律、人工智能和大数据分析)扩展了界定可行理性空间的边界。由于这种理性边界的扩展，机器自动决策使市场更有效率。
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From a computational point of view, decision procedures can be encoded in [[algorithms]] and [[heuristics]]. [[Edward Tsang]] argues that the effective rationality of an agent is determined by its [[computational intelligence]]. Everything else being equal, an agent that has better algorithms and heuristics could make "more rational" (more optimal) decisions than one that has poorer heuristics and algorithms.<ref>{{cite journal |doi=10.1007/s11633-008-0063-6 |author=Tsang, E.P.K. |title=Computational intelligence determines effective rationality |journal= International Journal of Automation and Computing|volume=5 |issue=1 |pages=63–6 |year=2008 |s2cid=9769519 }}</ref> [[Tshilidzi Marwala]] and [[Evan Hurwitz]] in their study on bounded rationality observed that advances in technology (e.g. computer processing power because of [[Moore's law]], [[artificial intelligence]] and big data analytics) expand the bounds that define the feasible rationality space. Because of this expansion of the bounds of rationality, machine automated decision making makes markets more efficient.<ref>{{cite book |last1=Marwala |first1= Tshilidzi| last2=Hurwitz |first2= Evan |title=Artificial Intelligence and Economic Theory: Skynet in the Market |year=2017 |publisher=[[Springer Science+Business Media|Springer]] |location=London |isbn=978-3-319-66104-9}}</ref>
  
  
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{{further|Behavioral economics}}
 
{{further|Behavioral economics}}
  
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Bounded rationality implies the idea that humans take reasoning shortcuts that may lead to suboptimal decision-making. Behavioral economists engage in mapping the decision shortcuts that agents use in order to help increase the effectiveness of human decision-making. One treatment of this idea comes from [[Cass Sunstein]] and [[Richard Thaler]]'s ''[[Nudge (book)|Nudge]]''.<ref>{{cite book|title=Nudge: Improving Decisions about Health, Wealth, and Happiness|isbn=978-0-14-311526-7|oclc=791403664|date=April 8, 2008|publisher=Yale University Press|authors=Thaler, Richard H., Sunstein, Cass R.|title-link=Nudge (book)}}</ref><ref>{{cite journal|title=Choice Architecture|authors=Thaler, Richard H., Sunstein, Cass R. and Balz, John P.|doi=10.2139/ssrn.1583509|ssrn=1583509|date=April 2, 2010}}</ref> Sunstein and Thaler recommend that choice architectures are modified in light of human agents' bounded rationality. A widely cited proposal from Sunstein and Thaler urges that healthier food be placed at sight level in order to increase the likelihood that a person will opt for that choice instead of a less healthy option. Some critics of ''Nudge'' have lodged attacks that modifying choice architectures will lead to people becoming worse decision-makers.<ref>{{cite web|last1=Wright|first1=Joshua|first2=Douglas|last2=Ginsberg|title=Free to Err?: Behavioral Law and Economics and its Implications for Liberty|url=http://www.libertylawsite.org/liberty-forum/free-to-err-behavioral-law-and-economics-and-its-implications-for-liberty/|date=February 16, 2012|work=Library of Law & Liberty}}</ref><ref>{{cite book|last1=Sunstein|first1=Cass|title=Going to extreems: How Like Minds Unite and Divide|url=https://books.google.com/?id=jEWplxVkEEEC|isbn=9780199793143|date=2009-05-13}}</ref>
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Bounded rationality implies the idea that humans take reasoning shortcuts that may lead to suboptimal decision-making. Behavioral economists engage in mapping the decision shortcuts that agents use in order to help increase the effectiveness of human decision-making. One treatment of this idea comes from [[Cass Sunstein]] and [[Richard Thaler]]'s ''[[Nudge (book)|Nudge]]''.<ref>{{cite book|title=Nudge: Improving Decisions about Health, Wealth, and Happiness|isbn=978-0-14-311526-7|oclc=791403664|date=April 8, 2008|publisher=Yale University Press|authors=Thaler, Richard H., Sunstein, Cass R.|title-link=Nudge (book)}}</ref><ref>{{cite journal|title=Choice Architecture|authors=Thaler, Richard H., Sunstein, Cass R. and Balz, John P.|doi=10.2139/ssrn.1583509|ssrn=1583509|date=April 2, 2010|s2cid=219382170}}</ref> Sunstein and Thaler recommend that choice architectures are modified in light of human agents' bounded rationality. A widely cited proposal from Sunstein and Thaler urges that healthier food be placed at sight level in order to increase the likelihood that a person will opt for that choice instead of a less healthy option. Some critics of ''Nudge'' have lodged attacks that modifying choice architectures will lead to people becoming worse decision-makers.<ref>{{cite web|last1=Wright|first1=Joshua|first2=Douglas|last2=Ginsberg|title=Free to Err?: Behavioral Law and Economics and its Implications for Liberty|url=http://www.libertylawsite.org/liberty-forum/free-to-err-behavioral-law-and-economics-and-its-implications-for-liberty/|date=February 16, 2012|work=Library of Law & Liberty}}</ref><ref>{{cite book|last1=Sunstein|first1=Cass|title=Going to extreems: How Like Minds Unite and Divide|url=https://books.google.com/books?id=jEWplxVkEEEC|isbn=9780199793143|date=2009-05-13}}</ref>
  
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Bounded rationality implies the idea that humans take reasoning shortcuts that may lead to suboptimal decision-making. Behavioral economists engage in mapping the decision shortcuts that agents use in order to help increase the effectiveness of human decision-making. One treatment of this idea comes from Cass Sunstein and Richard Thaler's Nudge. Sunstein and Thaler recommend that choice architectures are modified in light of human agents' bounded rationality. A widely cited proposal from Sunstein and Thaler urges that healthier food be placed at sight level in order to increase the likelihood that a person will opt for that choice instead of a less healthy option. Some critics of Nudge have lodged attacks that modifying choice architectures will lead to people becoming worse decision-makers.
 
  
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有限理性意味着人类走了一条可能导致次优决策的推理捷径。行为经济学家从事绘制决策捷径，代理人使用，以帮助提高人类决策的有效性。卡斯 · 桑斯坦和理查德 · 塞勒对这个观点的一个论述来自《轻推》。和 Thaler 建议，选择的结构应该根据人类代理人的有限理性进行修改。一个被广泛引用的来自 Sunstein 和 Thaler 的建议是，把更健康的食物放在视线范围内，以增加一个人选择健康食物的可能性，而不是一个不太健康的选择。一些对 Nudge 持批评态度的人指出，修改选择架构将导致人们成为更糟糕的决策者。
 
  
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Bounded rationality was shown to be essential to predict human sociability properties in a particular model by [[Vernon L. Smith]] and Michael J. Campbell.<ref name = "CaSm">
  
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{{cite journal|author1 = Michael J. Campbell | author2 = [[Vernon L. Smith]] | title = An elementary humanomics approach to boundedly rational quadratic models | journal = Physica A |year=2020|doi=10.1016/j.physa.2020.125309| url =https://www.researchgate.net/publication/343657559_An_Elementary_Humanomics_Approach_to_Boundedly_Rational_Quadratic_Models}}</ref> There, an agent-based model correctly predicts that agents are averse to resentment and punishment, and that there is an asymmetry between gratitude/reward and resentment/punishment.  The purely rational Nash equilibrium is shown to have ''no'' predictive power for that model, and the boundedly rational [[Gibbs measure|Gibbs equilibrium]] must be used to predict phenomena outlined in ''Humanomics''.<ref name = "SmWi">{{cite book|author = [[Vernon L. Smith]] and [[Bart J. Wilson]]|date=2019|title=Humanomics: Moral Sentiments and the Wealth of Nations for the Twenty-First Century|url=https://www.cambridge.org/core/books/humanomics/1B4064A206BD99DB36E794B53ADF8BB4|doi = 10.1017/9781108185561|publisher=Cambridge University Press}}</ref>
  
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==Influence on social network structure==
 
  
  
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==Influence on social network structure==
  
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Recent research has shown that bounded rationality of individuals may influence the topology of the social networks that evolve among them. In particular, Kasthurirathna and Piraveenan<ref>{{cite journal |last1=Kasthurirathna|first1=Dharshana  |last2=Piraveenan |first2=Mahendra. |title=Emergence of scale-free characteristics in socioecological systems with bounded rationality |journal=[[Scientific Reports (journal)|Scientific Reports]] |volume=7 |date=2015}}</ref> have shown that in socio-ecological systems, the drive towards improved rationality on average might be an evolutionary reason for the emergence of scale-free properties. They did this by simulating a number of strategic games on an initially random network with distributed bounded rationality, then re-wiring the network so that the network on average converged towards Nash equilibria, despite the bounded rationality of nodes. They observed that this re-wiring process results in scale-free networks. Since scale-free networks are ubiquitous in social systems, the link between bounded rationality distributions and social structure is an important one in explaining social phenomena.
 
  
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Recent research has shown that bounded rationality of individuals may influence the topology of the social networks that evolve among them. In particular, Kasthurirathna and Piraveenan have shown that in socio-ecological systems, the drive towards improved rationality on average might be an evolutionary reason for the emergence of scale-free properties. They did this by simulating a number of strategic games on an initially random network with distributed bounded rationality, then re-wiring the network so that the network on average converged towards Nash equilibria, despite the bounded rationality of nodes. They observed that this re-wiring process results in scale-free networks. Since scale-free networks are ubiquitous in social systems, the link between bounded rationality distributions and social structure is an important one in explaining social phenomena.
 
  
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最近的研究表明，个体的有限理性可能会影响其中进化的社交网络的拓扑结构。特别是，Kasthurirathna 和 Piraveenan 已经表明，在社会生态系统中，平均而言，改善理性的驱动力可能是无尺度特性出现的进化原因。他们这样做是通过模拟一个最初的随机网络上的一些策略游戏和分布式有限理性，然后重新布线网络，使网络平均收敛到纳什均衡，尽管有有限理性的节点。他们观察到，这种重新布线的过程导致了无标度网络。由于无标度网络在社会系统中无处不在，有限理性分布和社会结构之间的联系是解释社会现象的一个重要因素。
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Recent research has shown that bounded rationality of individuals may influence the topology of the social networks that evolve among them. In particular, Kasthurirathna and Piraveenan<ref>{{Cite journal|last1=Kasthurirathna|first1=Dharshana|last2=Piraveenan|first2=Mahendra|date=2015-06-11|title=Emergence of scale-free characteristics in socio-ecological systems with bounded rationality|journal=Scientific Reports|language=en|volume=5|issue=1|page=10448|doi=10.1038/srep10448|pmid=26065713|pmc=4464151|issn=2045-2322|doi-access=free}}</ref> have shown that in socio-ecological systems, the drive towards improved rationality on average might be an evolutionary reason for the emergence of scale-free properties. They did this by simulating a number of strategic games on an initially random network with distributed bounded rationality, then re-wiring the network so that the network on average converged towards Nash equilibria, despite the bounded rationality of nodes. They observed that this re-wiring process results in scale-free networks. Since scale-free networks are ubiquitous in social systems, the link between bounded rationality distributions and social structure is an important one in explaining social phenomena.
  
  
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* ''[[Administrative Behavior]]''
 
* ''[[Administrative Behavior]]''
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* ''[[Homo economicus]]''
 
* ''[[Homo economicus]]''
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* [[Memetics]]
 
* [[Memetics]]
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* [[Utility maximization problem]]
 
* [[Utility maximization problem]]
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* {{cite book |author=Elster, Jon |title=Sour Grapes: Studies in the Subversion of Rationality |publisher=Cambridge University Press |location=Cambridge, UK |year=1983 |isbn=978-0-521-25230-0 }}
 
* {{cite book |author=Elster, Jon |title=Sour Grapes: Studies in the Subversion of Rationality |publisher=Cambridge University Press |location=Cambridge, UK |year=1983 |isbn=978-0-521-25230-0 }}
  
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* {{cite book |author1=Gigerenzer, Gerd  |author2=Selten, Reinhard  |lastauthoramp=yes |title=Bounded Rationality |publisher=[[MIT Press]] |location=Cambridge |year=2002 |isbn=978-0-262-57164-7 }}
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* Felin, T., Koenderink, J., & Krueger, J. (2017). "Rationality, perception and the all-seeing eye." ''Psychonomic Bulletin and Review'', 25: 1040-1059. [https://link.springer.com/article/10.3758/s13423-016-1198-z DOI 10.3758/s13423-016-1198-z]
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* Gershman, S.J., Horvitz, E.J., & Tenenbaum, J.B. (2015). Computational rationality: A converging paradigm for intelligence in brains, minds, and machines. ''Science,'' 49: 273-278. [https://science.sciencemag.org/content/349/6245/273.abstract DOI: 10.1126/science.aac6076]
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* {{cite book |author1=Gigerenzer, Gerd  |author2=Selten, Reinhard  |name-list-style=amp |title=Bounded Rationality |publisher=[[MIT Press]] |location=Cambridge |year=2002 |isbn=978-0-262-57164-7 }}
  
 
* Hayek, F.A (1948) Individualism and Economic order
 
* Hayek, F.A (1948) Individualism and Economic order
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* Simon, Herbert (1957). "A Behavioral Model of Rational Choice", in Models of Man, Social and Rational: Mathematical Essays on Rational Human Behavior in a Social Setting. New York: Wiley.
 
* Simon, Herbert (1957). "A Behavioral Model of Rational Choice", in Models of Man, Social and Rational: Mathematical Essays on Rational Human Behavior in a Social Setting. New York: Wiley.
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* {{cite book |author1=March, James G.  |author2=Simon, Herbert  |lastauthoramp=yes | title=Organizations  |publisher=John Wiley and Sons |year=1958 |isbn=978-0-471-56793-6 }}
 
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* {{cite journal |doi=10.1126/science.2270480 |author=Simon, Herbert |title=A mechanism for social selection and successful altruism |journal=Science |volume=250 |issue=4988 |pages=1665–8 |year=1990 |pmid=2270480 }}
 
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* {{cite journal |doi=10.1287/orsc.2.1.125 |author=Simon, Herbert |title=Bounded Rationality and Organizational Learning |journal=Organization Science |volume=2 |issue=1 |pages=125–134 |year=1991 }}
 
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* {{cite book |author=Tisdell, Clem |title=Bounded Rationality and Economic Evolution: A Contribution to Decision Making, Economics, and Management |publisher=Brookfield |location=Cheltenham, UK |year=1996 |isbn=978-1-85898-352-3 }}
 
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* {{cite encyclopedia |last1=Wheeler |first1=Gregory |authorlink1= Gregory Wheeler | editor= [[Edward Zalta]] |encyclopedia=[[Stanford Encyclopedia of Philosophy]] | title=Bounded Rationality |url=https://plato.stanford.edu/entries/bounded-rationality |year=2018 |location= Stanford, CA}}
 
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* {{cite journal |author=Williamson, Oliver E.|title=The economics of organization: the transaction cost approach |journal=American Journal of Sociology |volume=87 |issue=3 |pages=[http://www.polisci.ucsd.edu/gcox/06%20Ollie.pdf 548–577] (press '''+''')|year=1981 |doi=10.1086/227496 }}
 
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* [http://choo.fis.utoronto.ca/FIS/courses/lis2149/kahneman.NobelPrize.pdf Mapping Bounded Rationality by Daniel Kahneman]
 
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* [http://www.huwdixon.org/SurfingEconomics/chapter7.pdf Artificial Intelligence and Economic Theory] chapter 7 of [http://huwdixon.org/SurfingEconomics/index.html Surfing Economics] by [[Huw Dixon]].
 
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* {{cite IEP |url-id=re-bo-ag |title=Resource Bounded Agents}}
 
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分类: 行为经济学
 
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* {{cite book |author1=March, James G.  |author2=Simon, Herbert  |name-list-style=amp | title=Organizations  |publisher=John Wiley and Sons |year=1958 |isbn=978-0-471-56793-6 }}
  
 
Category:Game theory
 
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范畴: 博弈论
 
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* {{cite journal |doi=10.1126/science.2270480 |author=Simon, Herbert |title=A mechanism for social selection and successful altruism |journal=Science |volume=250 |issue=4988 |pages=1665–8 |year=1990 |pmid=2270480 }}
  
 
Category:Rational choice theory
 
Category:Rational choice theory

2020年10月25日 (日) 21:15的版本

此词条暂由彩云小译翻译，翻译字数共759，未经人工整理和审校，带来阅读不便，请见谅。

Bounded rationality is the idea that rationality is limited, when individuals make decisions, by the tractability of the decision problem, the cognitive limitations of the mind, and the time available to make the decision. Decision-makers, in this view, act as satisficers, seeking a satisfactory solution rather than an optimal one.

Bounded rationality is the idea that rationality is limited, when individuals make decisions, by the tractability of the decision problem, the cognitive limitations of the mind, and the time available to make the decision. Decision-makers, in this view, act as satisficers, seeking a satisfactory solution rather than an optimal one.

有限理性是这样一种观点，即当个体做出决定时，理性是有限的，受决定问题的可控性、大脑的认知局限性以及做出决定的可用时间的限制。这种观点认为，决策者作为满足者，寻求一个令人满意的解决方案，而不是一个最佳的解决方案。


Herbert A. Simon proposed bounded rationality as an alternative basis for the mathematical modeling of decision-making, as used in economics, political science and related disciplines. It complements "rationality as optimization", which views decision-making as a fully rational process of finding an optimal choice given the information available.[1] Simon used the analogy of a pair of scissors, where one blade represents "cognitive limitations" of actual humans and the other the "structures of the environment", illustrating how minds compensate for limited resources by exploiting known structural regularity in the environment.[1] Many economics models assume that people are on average rational, and can in large enough quantities be approximated to act according to their preferences. With bounded rationality, Simon's goal was "to replace the global rationality of economic man with a kind of rational behavior that is compatible with the access to information and the computational capacities that are actually possessed by organisms, including man, in the kinds of environments in which such organisms exist."[2] In short, the concept of bounded rationality revises notions of "perfect" rationality to account for the fact that perfectly rational decisions are often not feasible in practice because of the intractability of natural decision problems and the finite computational resources available for making them.

Herbert A. Simon proposed bounded rationality as an alternative basis for the mathematical modeling of decision-making, as used in economics, political science and related disciplines. It complements "rationality as optimization", which views decision-making as a fully rational process of finding an optimal choice given the information available. Many economics models assume that people are on average rational, and can in large enough quantities be approximated to act according to their preferences. With bounded rationality, Simon's goal was "to replace the global rationality of economic man with a kind of rational behavior that is compatible with the access to information and the computational capacities that are actually possessed by organisms, including man, in the kinds of environments in which such organisms exist."

赫伯特·西蒙提出有限理性作为决策的数学建模的替代基础，用于经济学、政治学和相关学科。它补充了“理性即优化”的观点，该观点认为，决策是一个完全理性的过程，找到一个最佳的选择给予信息。许多经济学模型假设人们一般都是理性的，并且可以大量地根据他们的偏好来近似地行动。通过有限理性，Simon 的目标是“用一种理性行为来取代经济人的全球理性，这种理性行为与有机体，包括人，在这种有机体存在的环境中实际拥有的信息获取和计算能力是相容的。”


The concept of bounded rationality continues to influence (and be debated in) different disciplines, including economics, psychology, law, political science and cognitive science.[3] Some models of human behavior in the social sciences assume that humans can be reasonably approximated or described as "rational" entities, as in rational choice theory or Downs Political Agency Models.[4]

Huw Dixon later argues that it may not be necessary to analyze in detail the process of reasoning underlying bounded rationality. If we believe that agents will choose an action that gets them "close" to the optimum, then we can use the notion of epsilon-optimization, which means we choose our actions so that the payoff is within epsilon of the optimum. If we define the optimum (best possible) payoff as [math]\displaystyle{ U^* }[/math], then the set of epsilon-optimizing options S(ε) can be defined as all those options s such that:

后来认为，也许没有必要详细分析有限理性的推理过程。如果我们相信代理人会选择一个让他们“接近”最优的行动，那么我们可以使用 epsilon 优化的概念，这意味着我们选择我们的行动，使得回报在最优的 epsilon 之内。如果我们将最优(最佳可能)收益定义为 < math > u ^ * </math > ，那么 epsilon-optimization 选项集 s (ε)就可以定义为所有这些选项:


Origins

[math]\displaystyle{ U(s) \geq U^*-\epsilon }[/math].

[ math ] u (s) geq u ^ *-epsilon.

The term was coined by Herbert A. Simon. In Models of Man, Simon points out that most people are only partly rational, and are irrational in the remaining part of their actions. In another work, he states "boundedly rational agents experience limits in formulating and solving complex problems and in processing (receiving, storing, retrieving, transmitting) information".[5] Simon describes a number of dimensions along which "classical" models of rationality can be made somewhat more realistic, while sticking within the vein of fairly rigorous formalization. These include:


The notion of strict rationality is then a special case (ε=0). The advantage of this approach is that it avoids having to specify in detail the process of reasoning, but rather simply assumes that whatever the process is, it is good enough to get near to the optimum.

严格合理性的概念是一个特例(ε = 0)。这种方法的优点在于，它避免了详细说明推理过程，而是简单地假设无论过程是什么，它都足以接近最优值。

  • limiting the types of utility functions
  • recognizing the costs of gathering and processing information

From a computational point of view, decision procedures can be encoded in algorithms and heuristics. Edward Tsang argues that the effective rationality of an agent is determined by its computational intelligence. Everything else being equal, an agent that has better algorithms and heuristics could make "more rational" (more optimal) decisions than one that has poorer heuristics and algorithms. Tshilidzi Marwala and Evan Hurwitz in their study on bounded rationality observed that advances in technology (e.g. computer processing power because of Moore's law, artificial intelligence and big data analytics) expand the bounds that define the feasible rationality space. Because of this expansion of the bounds of rationality, machine automated decision making makes markets more efficient.

从计算的角度来看，决策过程可以编码在算法和启发式。曾德昌认为，智能体的有效合理性取决于其计算智能。在其他条件相同的情况下，一个拥有更好的算法和启发式的智能体可以比那些启发式和算法较差的智能体做出“更理性”(更优化)的决策。和 Evan Hurwitz 在他们关于有限理性的研究中观察到技术的进步(例如:。由于摩尔定律、人工智能和大数据分析等因素的影响，计算机处理能力扩展了界定可行理性空间的范围。由于这种理性边界的扩展，机器自动决策使市场更有效率。

  • the possibility of having a "vector" or "multi-valued" utility function


Simon suggests that economic agents use heuristics to make decisions rather than a strict rigid rule of optimization. They do this because of the complexity of the situation.


Bounded rationality implies the idea that humans take reasoning shortcuts that may lead to suboptimal decision-making. Behavioral economists engage in mapping the decision shortcuts that agents use in order to help increase the effectiveness of human decision-making. One treatment of this idea comes from Cass Sunstein and Richard Thaler's Nudge. Sunstein and Thaler recommend that choice architectures are modified in light of human agents' bounded rationality. A widely cited proposal from Sunstein and Thaler urges that healthier food be placed at sight level in order to increase the likelihood that a person will opt for that choice instead of a less healthy option. Some critics of Nudge have lodged attacks that modifying choice architectures will lead to people becoming worse decision-makers.

有限理性意味着人类走了一条可能导致次优决策的推理捷径。行为经济学家从事绘制决策捷径，代理人使用，以帮助提高人类决策的有效性。卡斯 · 桑斯坦和理查德 · 塞勒对这一观点的一种论述来自《轻推》。和 Thaler 建议选择的结构应该根据人类代理的有限理性来修改。桑斯坦和泰勒提出的一个被广泛引用的建议是，为了增加人们选择健康食品而不是不健康食品的可能性，应该把健康食品放在视线范围内。一些对 Nudge 持批评态度的人指出，修改选择架构将导致人们成为更糟糕的决策者。

Model extensions

Bounded rationality was shown to be essential to predict human sociability properties in a particular model by Vernon L. Smith and Michael J. Campbell. There, an agent-based model correctly predicts that agents are averse to resentment and punishment, and that there is an asymmetry between gratitude/reward and resentment/punishment. The purely rational Nash equilibrium is shown to have no predictive power for that model, and the boundedly rational Gibbs equilibrium must be used to predict phenomena outlined in Humanomics.

由 Vernon l. Smith 和 Michael j. Campbell 研究表明，在一个特定的模型中，有限理性对于预测人类的社交能力是必不可少的。在这里，个体为本模型预测正确地预测了代理人厌恶怨恨和惩罚，并且在感激/奖励和怨恨/惩罚之间存在着不对称。纯理性的纳什均衡点对于这个模型没有预测能力，有限理性的吉布斯平衡必须用来预测在 Humanomics 概述的现象。

As decision-makers have to make decisions about how and when to decide, Ariel Rubinstein proposed to model bounded rationality by explicitly specifying decision-making procedures.[6] This puts the study of decision procedures on the research agenda.


Gerd Gigerenzer opines that decision theorists have not really adhered to Simon's original ideas. Rather, they have considered how decisions may be crippled by limitations to rationality, or have modeled how people might cope with their inability to optimize. Gigerenzer proposes and shows that simple heuristics often lead to better decisions than theoretically optimal procedures.[4]


Recent research has shown that bounded rationality of individuals may influence the topology of the social networks that evolve among them. In particular, Kasthurirathna and Piraveenan have shown that in socio-ecological systems, the drive towards improved rationality on average might be an evolutionary reason for the emergence of scale-free properties. They did this by simulating a number of strategic games on an initially random network with distributed bounded rationality, then re-wiring the network so that the network on average converged towards Nash equilibria, despite the bounded rationality of nodes. They observed that this re-wiring process results in scale-free networks. Since scale-free networks are ubiquitous in social systems, the link between bounded rationality distributions and social structure is an important one in explaining social phenomena.

最近的研究表明，个体的有限理性可能会影响其中进化的社交网络的拓扑结构。特别是，Kasthurirathna 和 Piraveenan 已经表明，在社会生态系统中，平均而言，改善理性的驱动力可能是无尺度特性出现的进化原因。他们通过模拟一个具有分布式有限理性的最初随机网络中的一系列策略游戏，然后重新布线网络，使网络平均收敛到纳什均衡，尽管节点有限理性很大。他们观察到，这种重新布线的过程导致了无标度网络。由于无标度网络在社会系统中无处不在，有限理性分布和社会结构之间的联系是解释社会现象的一个重要因素。

Huw Dixon later argues that it may not be necessary to analyze in detail the process of reasoning underlying bounded rationality.[7] If we believe that agents will choose an action that gets them "close" to the optimum, then we can use the notion of epsilon-optimization, which means we choose our actions so that the payoff is within epsilon of the optimum. If we define the optimum (best possible) payoff as [math]\displaystyle{ U^* }[/math], then the set of epsilon-optimizing options S(ε) can be defined as all those options s such that:


[math]\displaystyle{ U(s) \geq U^*-\epsilon }[/math].


Notes

  1. ↑ 1.0 1.1 Gigerenzer, Gerd; Selten, Reinhard (2002). Bounded Rationality: The Adaptive Toolbox. MIT Press. ISBN 978-0-262-57164-7. https://books.google.com/books?id=dVMq5UoYS3YC&dq=%22bounded+rationality%22&printsec=frontcover. 
  2. ↑ Simon, Herbert A. (1955-02-01). "A Behavioral Model of Rational Choice". The Quarterly Journal of Economics (in English). 69 (1): 99–118. doi:10.2307/1884852. ISSN 0033-5533. JSTOR 1884852.
  3. ↑ Chater, Nick; Felin, Teppo; Funder, David C.; Gigerenzer, Gerd; Koenderink, Jan J.; Krueger, Joachim I.; Noble, Denis; Nordli, Samuel A.; Oaksford, Mike; Schwartz, Barry; Stanovich, Keith E. (2018-04-01). "Mind, rationality, and cognition: An interdisciplinary debate". Psychonomic Bulletin & Review (in English). 25 (2): 793–826. doi:10.3758/s13423-017-1333-5. ISSN 1531-5320. PMC 5902517. PMID 28744767.
  4. ↑ 4.0 4.1 Mancur Olson, Jr. ([1965] 1971). The Logic of Collective Action: Public Goods and the Theory of Groups, 2nd ed. Harvard University Press, Description, Table of Contents, and preview.
  5. ↑ Oliver E. Williamson, p. 553, citing Simon.
  6. ↑ Rubinstein, Ariel (1997). Modeling bounded rationality. MIT Press. ISBN 9780262681001. http://arielrubinstein.tau.ac.il/book-br.html. 
  7. ↑ Moss; Rae, eds. (1992). "Some Thoughts on Artificial Intelligence and Economic Theory". Artificial Intelligence and Economic Analysis. Edward Elgar. pp. 131–154. ISBN 978-1852786854. https://archive.org/details/artificialintell0000unse_a9c0/page/131. 
  8. ↑ Tsang, E.P.K. (2008). "Computational intelligence determines effective rationality". International Journal of Automation and Computing. 5 (1): 63–6. doi:10.1007/s11633-008-0063-6. S2CID 9769519.
  9. ↑ Marwala, Tshilidzi; Hurwitz, Evan (2017). Artificial Intelligence and Economic Theory: Skynet in the Market. London: Springer. ISBN 978-3-319-66104-9. 
  10. ↑ Thaler, Richard H., Sunstein, Cass R. (April 8, 2008). Nudge: Improving Decisions about Health, Wealth, and Happiness. Yale University Press. ISBN 978-0-14-311526-7. OCLC 791403664. 
  11. ↑ Thaler, Richard H., Sunstein, Cass R. and Balz, John P. (April 2, 2010). "Choice Architecture". doi:10.2139/ssrn.1583509. S2CID 219382170. SSRN 1583509. {{cite journal}}: Cite journal requires |journal= (help)CS1 maint: uses authors parameter (link)
  12. ↑ Wright, Joshua; Ginsberg, Douglas (February 16, 2012). "Free to Err?: Behavioral Law and Economics and its Implications for Liberty". Library of Law & Liberty.
  13. ↑ Sunstein, Cass (2009-05-13). Going to extreems: How Like Minds Unite and Divide. ISBN 9780199793143. https://books.google.com/books?id=jEWplxVkEEEC. 
  14. ↑ Michael J. Campbell; Vernon L. Smith (2020). "An elementary humanomics approach to boundedly rational quadratic models". Physica A. doi:10.1016/j.physa.2020.125309.
  15. ↑ Vernon L. Smith and Bart J. Wilson (2019). Humanomics: Moral Sentiments and the Wealth of Nations for the Twenty-First Century. Cambridge University Press. doi:10.1017/9781108185561. https://www.cambridge.org/core/books/humanomics/1B4064A206BD99DB36E794B53ADF8BB4. 
  16. ↑ Kasthurirathna, Dharshana; Piraveenan, Mahendra (2015-06-11). "Emergence of scale-free characteristics in socio-ecological systems with bounded rationality". Scientific Reports (in English). 5 (1): 10448. doi:10.1038/srep10448. ISSN 2045-2322. PMC 4464151. PMID 26065713.


Further reading

  • Elster, Jon (1983). Sour Grapes: Studies in the Subversion of Rationality. Cambridge, UK: Cambridge University Press. ISBN 978-0-521-25230-0. 
  • Felin, T., Koenderink, J., & Krueger, J. (2017). "Rationality, perception and the all-seeing eye." Psychonomic Bulletin and Review, 25: 1040-1059. DOI 10.3758/s13423-016-1198-z
  • Gershman, S.J., Horvitz, E.J., & Tenenbaum, J.B. (2015). Computational rationality: A converging paradigm for intelligence in brains, minds, and machines. Science, 49: 273-278. DOI: 10.1126/science.aac6076
  • Hayek, F.A (1948) Individualism and Economic order
  • Simon, Herbert (1957). "A Behavioral Model of Rational Choice", in Models of Man, Social and Rational: Mathematical Essays on Rational Human Behavior in a Social Setting. New York: Wiley.

Category:Behavioral economics

分类: 行为经济学

Category:Game theory

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