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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.
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.
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 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，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必须用来预测在 Humanomics 概述的现象。
==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 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.
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.
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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