有限理性
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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.
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。
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. 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.
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.
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。
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.[2]
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.
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。
Origins
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".[3] 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". 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:
- limiting the types of utility functions
- recognizing the costs of gathering and processing information
- 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.
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。
Model extensions
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.[4] 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. 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。
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.[2]
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.
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。
Huw Dixon later argues that it may not be necessary to analyze in detail the process of reasoning underlying bounded rationality.[5] 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:
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 ()可以定义为所有这些选项，如下:
[math]\displaystyle{ U(s) \geq U^*-\epsilon }[/math].
[math]\displaystyle{ U(s) \geq U^*-\epsilon }[/math].
数学 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.
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.
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。
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.[6] 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.[7]
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。
Relationship to behavioral economics
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.[8][9] 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.[10][11]
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。
Influence on social network structure
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[12] 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.
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。
See also
Notes
- ↑ 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/?id=dVMq5UoYS3YC&dq=%22bounded+rationality%22&printsec=frontcover.
- ↑ 2.0 2.1 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.
- ↑ Oliver E. Williamson, p. 553, citing Simon.
- ↑ Rubinstein, Ariel (1997). Modeling bounded rationality. MIT Press. ISBN 9780262681001. http://arielrubinstein.tau.ac.il/book-br.html.
- ↑ 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.
- ↑ 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.
- ↑ Marwala, Tshilidzi; Hurwitz, Evan (2017). Artificial Intelligence and Economic Theory: Skynet in the Market. London: Springer. ISBN 978-3-319-66104-9.
- ↑ 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.
- ↑ Thaler, Richard H., Sunstein, Cass R. and Balz, John P. (April 2, 2010). "Choice Architecture". doi:10.2139/ssrn.1583509. SSRN 1583509.
{{cite journal}}: Cite journal requires|journal=(help)CS1 maint: uses authors parameter (link) - ↑ Wright, Joshua; Ginsberg, Douglas (February 16, 2012). "Free to Err?: Behavioral Law and Economics and its Implications for Liberty". Library of Law & Liberty.
- ↑ Sunstein, Cass (2009-05-13). Going to extreems: How Like Minds Unite and Divide. ISBN 9780199793143. https://books.google.com/?id=jEWplxVkEEEC.
- ↑ Kasthurirathna, Dharshana; Piraveenan, Mahendra. (2015). "Emergence of scale-free characteristics in socioecological systems with bounded rationality". Scientific Reports. 7.
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.
- 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.
Category:Behavioral economics
分类: 行为经济学
Category:Game theory
范畴: 博弈论
Category:Rational choice theory
范畴: 理性选择理论
This page was moved from wikipedia:en:Bounded rationality. Its edit history can be viewed at 有限理性/edithistory