“有限理性”的版本间的差异
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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 [[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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'''有限理性'''是这样一种观点，即当个体做出决定时，受决定问题的可控性、大脑的认知局限性以及决定时间的限制，'''<font color="#ff8000">理性 Rationality</font>'''是有限的。这种观点认为，决策者会作为'''<font color="#ff8000">满足者 Satisficer</font>'''，寻求一个令人满意的而不是最佳的解决方案。 | '''有限理性'''是这样一种观点，即当个体做出决定时，受决定问题的可控性、大脑的认知局限性以及决定时间的限制，'''<font color="#ff8000">理性 Rationality</font>'''是有限的。这种观点认为，决策者会作为'''<font color="#ff8000">满足者 Satisficer</font>'''，寻求一个令人满意的而不是最佳的解决方案。 | ||
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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/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. | + | [[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 name=":0">{{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. |
| − | Herbert A. Simon | + | '''<font color="#ff8000">赫伯特·A·西蒙 Herbert A. Simon</font>'''提出把有限理性作为'''<font color="#ff8000">决策 Decision-making</font>'''数学模型的替代基础，用于'''<font color="#ff8000">经济学 Economics</font>'''、'''<font color="#ff8000">政治学 Political Science</font>'''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，根据已有信息找到最佳选择的过程。<ref name="bounded_rationality_1999" />西蒙用一把剪刀作类比，其中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。<ref name="bounded_rationality_1999" />许多经济学模型假设人们一般都是理性的，并且可以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，这种理性行为在有机体（包括人类）存在的环境中实际拥有的信息获取和计算能力是相容的。”<ref name=":0" />简而言之，有限理性的概念修正了“完美”理性的概念以解释这样一个事实，由于自然决策问题的难解性和有限的计算资源，完全理性的决策在实践中往往不可行。 |
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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 name=":1">{{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> | ||
| − | + | 有限理性的概念继续影响着不同的学科，包括经济学、心理学、法律、政治学和认知科学。<ref name=":1" />'''<font color="#ff8000">社会科学 Social Science</font>'''中的一些'''<font color="#ff8000">人类行为 Human Behavior</font>'''模型假定，人类可以被合理地近似或描述为“理性”实体，例如'''<font color="#ff8000">理性选择理论 Rational Choice Theory</font>'''或唐斯政治机构模型。<ref name="Olson" /> | |
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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]]".<ref>[[Oliver E. Williamson]], p. 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 name=":2">[[Oliver E. Williamson]], p. 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: |
| − | + | 这个术语是由'''<font color="#ff8000">Herbert A.Simon 赫伯特·A·西蒙</font>'''创造的。在''《人类模型》''一书中，西蒙指出，大多数人的行为只是部分理性的，其余是非理性的。在另一部著作中，他指出“有限理性的行为主体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”。<ref name=":2" />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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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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西蒙认为，经济行为主体使用'''<font color="#ff8000">启发式 heuristic</font>'''而不是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。 | 西蒙认为，经济行为主体使用'''<font color="#ff8000">启发式 heuristic</font>'''而不是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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| − | 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. | + | 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 name=":3">{{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. |
| − | + | 由于决策者必须决定如何以及何时做出决定，'''<font color="#ff8000">阿里埃勒·鲁宾斯坦 Ariel Rubinstein</font>'''提议通过明确规定决策程序来建立有限理性的模型。<ref name=":3" />这就把决策程序的研究提上了研究日程。 | |
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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"/> | ||
| − | Gerd Gigerenzer | + | '''<font color="#ff8000">格尔德·吉格伦泽 Gerd Gigerenzer</font>'''认为，决策论专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式算法往往能比理论上的最佳程序获得更好的决策。如果我们相信行为主体会选择一个让他们“接近”最优的行动，那么我们可以使用 epsilon 优化的概念——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:<ref name="Olson" /> |
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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: | + | [[Huw Dixon]] later argues that it may not be necessary to analyze in detail the process of reasoning underlying bounded rationality.<ref name=":4">{{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: |
<math>U(s)\geq U^*-\epsilon</math>. | <math>U(s)\geq U^*-\epsilon</math>. | ||
| − | [ | + | [[Huw Dixon]]后来辩称，可能没有必要详细分析作为有限理性基础的推理过程。<ref name=":4" /> 如果我们相信代理会选择一个让他们“接近”最优值的动作，那么我们可以使用''epsilon-optimization''的概念，这意味着我们选择我们的动作，使得收益在最优值的 epsilon 内。如果我们将最优（最佳）收益定义为，那么一组 epsilon 优化选项'''S(ε)'''可以定义为所有这些选项'''s'''，使得： |
| + | <math>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. | ||
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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 name=":5">{{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 name=":6">{{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. | ||
| − | + | 从计算的角度来看，决策过程可以在'''<font color="#ff8000">算法 algorithm</font>'''和'''<font color="#ff8000">启发式 heuristic</font>'''上编码。'''<font color="#ff8000">曾德昌 Edward Tsang</font>'''认为，智能体的有效合理性取决于其'''<font color="#ff8000">计算智能 computational intelligence</font>'''。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。<ref name=":5" />他和 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。<ref name=":6" /> | |
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| − | 从计算的角度来看，决策过程可以在'''<font color="#ff8000">算法 algorithm</font>'''和'''<font color="#ff8000">启发式 heuristic</font>'''上编码。'''<font color="#ff8000">曾德昌 Edward Tsang</font>'''认为，智能体的有效合理性取决于其'''<font color="#ff8000">计算智能 computational intelligence</font>'''。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) | ||
==Relationship to behavioral economics== | ==Relationship to behavioral economics== | ||
| − | 与行为经济学的关系 | + | 与行为经济学的关系. |
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| − | Bounded rationality | + | 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 name=":7">{{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 name=":8">{{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 name=":9">{{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 name=":10">{{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> |
| + | 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，给行动主体使用以帮助提高人类决策的有效性。对这一观点的论述来自于卡斯·桑斯坦和理查德·塞勒的《Nudge》。<ref name=":7" /><ref name=":8" />Sunstein 和 Thaler 建议选择的结构应该根据人类行为主体的有限理性来修改。Sunstein 和 Thaler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。<ref name=":9" /><ref name=":10" /> | ||
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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"> | ||
| + | {{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> | ||
| − | 由 Vernon l. Smith 和 Michael j. Campbell | + | 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。<ref name="CaSm" />在这里，一个基于个体的模型正确地预测了行为主体反对怨恨和惩罚，并且在感激/奖励和怨恨/惩罚之间存在着不对称的情况。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'''<font color="#ff8000">吉布斯平衡 Gibbs equilibrium</font>'''必须在 Humanomics 概述的现象中进行预测。<ref name="SmWi" /> |
==Influence on social network structure== | ==Influence on social network structure== | ||
对社会网络结构的影响 | 对社会网络结构的影响 | ||
| − | |||
| − | |||
| − | |||
| + | Recent research has shown that bounded rationality of individuals may influence the topology of the social networks that evolve among them. In particular, Kasthurirathna<ref name=":11">{{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> 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在他们之间演化的社交网络的拓扑结构。特别的，Kasthurirathna <ref name=":11" />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。他们通过在一个具有分布式有限理性的初始随机网络上模拟一系列策略游戏，之后重新布线网络，使网络平均收敛到纳什平衡，尽管节点存在有限理性。他们观察到，这种重新布线的过程导致了无标度网络。因此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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2021年9月20日 (一) 14:40的版本
此词条暂由小竹凉翻译，翻译字数共1006，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.
有限理性是这样一种观点，即当个体做出决定时，受决定问题的可控性、大脑的认知局限性以及决定时间的限制，理性 Rationality是有限的。这种观点认为，决策者会作为满足者 Satisficer，寻求一个令人满意的而不是最佳的解决方案。
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.
赫伯特·A·西蒙 Herbert A. Simon提出把有限理性作为决策 Decision-making数学模型的替代基础，用于经济学 Economics、政治学 Political Science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，根据已有信息找到最佳选择的过程。[1]西蒙用一把剪刀作类比，其中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。[1]许多经济学模型假设人们一般都是理性的，并且可以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，这种理性行为在有机体（包括人类）存在的环境中实际拥有的信息获取和计算能力是相容的。”[2]简而言之，有限理性的概念修正了“完美”理性的概念以解释这样一个事实，由于自然决策问题的难解性和有限的计算资源，完全理性的决策在实践中往往不可行。
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]
有限理性的概念继续影响着不同的学科，包括经济学、心理学、法律、政治学和认知科学。[3]社会科学 Social Science中的一些人类行为 Human Behavior模型假定，人类可以被合理地近似或描述为“理性”实体，例如理性选择理论 Rational Choice Theory或唐斯政治机构模型。[4]
Origins
起源
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:
这个术语是由Herbert A.Simon 赫伯特·A·西蒙创造的。在《人类模型》一书中，西蒙指出，大多数人的行为只是部分理性的，其余是非理性的。在另一部著作中，他指出“有限理性的行为主体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”。[5]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:
- limiting the types of utility functions 限制效用 utility函数的类型
- recognizing the costs of gathering and processing information 认识到收集和处理信息的成本
- the possibility of having a "vector" or "multi-valued" utility function 向量 vector或多值效用函数的可能性
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.
西蒙认为，经济行为主体使用启发式 heuristic而不是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。
Model extensions
模型扩展
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.
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 Ariel Rubinstein提议通过明确规定决策程序来建立有限理性的模型。[6]这就把决策程序的研究提上了研究日程。
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]
格尔德·吉格伦泽 Gerd Gigerenzer认为，决策论专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式算法往往能比理论上的最佳程序获得更好的决策。如果我们相信行为主体会选择一个让他们“接近”最优的行动，那么我们可以使用 epsilon 优化的概念——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]\displaystyle{ u^* }[/math]，那么 epsilon-optimization 选项集s(ε)就可以定义为所有这些选项:[4]
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].
Huw Dixon后来辩称，可能没有必要详细分析作为有限理性基础的推理过程。[7] 如果我们相信代理会选择一个让他们“接近”最优值的动作，那么我们可以使用epsilon-optimization的概念，这意味着我们选择我们的动作，使得收益在最优值的 epsilon 内。如果我们将最优（最佳）收益定义为，那么一组 epsilon 优化选项S(ε)可以定义为所有这些选项s，使得：
[math]\displaystyle{ U(s)\geq U^*-\epsilon }[/math].
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)。虽然这种方法的优点在于避免了详细说明推理过程，但是它简单地假设无论过程是什么，都足以接近最优值。
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.[8] 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.[9]
从计算的角度来看，决策过程可以在算法 algorithm和启发式 heuristic上编码。曾德昌 Edward Tsang认为，智能体的有效合理性取决于其计算智能 computational intelligence。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。[8]他和 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。[9]
Relationship to behavioral economics
与行为经济学的关系.
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.[10][11] 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.[12][13]
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，给行动主体使用以帮助提高人类决策的有效性。对这一观点的论述来自于卡斯·桑斯坦和理查德·塞勒的《Nudge》。[10][11]Sunstein 和 Thaler 建议选择的结构应该根据人类行为主体的有限理性来修改。Sunstein 和 Thaler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。[12][13]
Bounded rationality was shown to be essential to predict human sociability properties in a particular model by Vernon L. Smith and Michael J. Campbell.[14] 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.[15]
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。[14]在这里，一个基于个体的模型正确地预测了行为主体反对怨恨和惩罚，并且在感激/奖励和怨恨/惩罚之间存在着不对称的情况。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 Gibbs equilibrium必须在 Humanomics 概述的现象中进行预测。[15]
Influence on social network structure
对社会网络结构的影响
Recent research has shown that bounded rationality of individuals may influence the topology of the social networks that evolve among them. In particular, Kasthurirathna[16] 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在他们之间演化的社交网络的拓扑结构。特别的，Kasthurirathna [16]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。他们通过在一个具有分布式有限理性的初始随机网络上模拟一系列策略游戏，之后重新布线网络，使网络平均收敛到纳什平衡，尽管节点存在有限理性。他们观察到，这种重新布线的过程导致了无标度网络。因此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。
==See also==
- Altruism 利他主义
- Analysis paralysis 分析瘫痪
- Ars longa, vita brevis 咒语：艺术是长久的,生命是短暂的
- Carnegie School 卡内基学校
- Concept driven strategy 概念驱动策略
- Cognitive bias 认知偏误
- Cognitive miser 认知吝啬
- Ecological rationality 生态合理性
- Elitism 精英主义
- Framing (social sciences) 框架(社会科学)
- Homo economicus 经济人假设
- Memetics 模因论
- Neoclassical economics 新古典主义经济学
- Organizing principle 组织原则
- Parametric determinism 参数决定论
- Priority heuristic 优先启发式
- Prospect theory 前景理论
- Psychohistory 心理史学
- Rational ignorance 理性忽略
- Satisficing 满意度
- Social heuristics Satisficing
- Subjective theory of value 价值的主观理论
- Substitution bias (psychology) 替代偏见(心理学)
- Transaction cost 交易成本
- Utility maximization problem 效用最大化问题
Notes
- ↑ 1.0 1.1 1.2 1.3 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.
- ↑ 2.0 2.1 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.
- ↑ 3.0 3.1 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.
- ↑ 4.0 4.1 4.2 4.3 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.
- ↑ 5.0 5.1 Oliver E. Williamson, p. 553, citing Simon.
- ↑ 6.0 6.1 Rubinstein, Ariel (1997). Modeling bounded rationality. MIT Press. ISBN 9780262681001. http://arielrubinstein.tau.ac.il/book-br.html.
- ↑ 7.0 7.1 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.
- ↑ 8.0 8.1 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.
- ↑ 9.0 9.1 Marwala, Tshilidzi; Hurwitz, Evan (2017). Artificial Intelligence and Economic Theory: Skynet in the Market. London: Springer. ISBN 978-3-319-66104-9.
- ↑ 10.0 10.1 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.
- ↑ 11.0 11.1 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) - ↑ 12.0 12.1 Wright, Joshua; Ginsberg, Douglas (February 16, 2012). "Free to Err?: Behavioral Law and Economics and its Implications for Liberty". Library of Law & Liberty.
- ↑ 13.0 13.1 Sunstein, Cass (2009-05-13). Going to extreems: How Like Minds Unite and Divide. ISBN 9780199793143. https://books.google.com/books?id=jEWplxVkEEEC.
- ↑ 14.0 14.1 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.
- ↑ 15.0 15.1 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.
- ↑ 16.0 16.1 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
- Bayer, R. C., Renner, E., & Sausgruber, R. (2009). Confusion and reinforcement learning in experimental public goods games. NRN working papers 2009–22, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
- 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
- Gigerenzer, Gerd; Selten, Reinhard (2002). Bounded Rationality. Cambridge: MIT Press. ISBN 978-0-262-57164-7.
- Hayek, F.A (1948) Individualism and Economic order
- Kahneman, Daniel (2003). "Maps of bounded rationality: psychology for behavioral economics" (PDF). The American Economic Review. 93 (5): 1449–75. CiteSeerX 10.1.1.194.6554. doi:10.1257/000282803322655392. Archived from the original (PDF) on 2018-02-19. Retrieved 2017-11-01.
- March, James G. (1994). A Primer on Decision Making: How Decisions Happen. New York: The Free Press. ISBN 978-0-02-920035-3. https://archive.org/details/primerondecision00marc.
- 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.
- March, James G.; Simon, Herbert (1958). Organizations. John Wiley and Sons. ISBN 978-0-471-56793-6.
- Simon, Herbert (1990). "A mechanism for social selection and successful altruism". Science. 250 (4988): 1665–8. doi:10.1126/science.2270480. PMID 2270480.
- Simon, Herbert (1991). "Bounded Rationality and Organizational Learning". Organization Science. 2 (1): 125–134. doi:10.1287/orsc.2.1.125.
- Tisdell, Clem (1996). Bounded Rationality and Economic Evolution: A Contribution to Decision Making, Economics, and Management. Cheltenham, UK: Brookfield. ISBN 978-1-85898-352-3.
- Wheeler, Gregory (2018). "Bounded Rationality". In Edward Zalta (ed.). Stanford Encyclopedia of Philosophy. Stanford, CA.
- Williamson, Oliver E. (1981). "The economics of organization: the transaction cost approach". American Journal of Sociology. 87 (3): 548–577 (press +). doi:10.1086/227496.
External links
- Artificial Intelligence and Economic Theory chapter 7 of Surfing Economics by Huw Dixon.
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