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摘要翻译：
经济是复杂的人为系统，其中有机体和市场根据尚未完全理解的动机和原则相互作用。对传统经济学的假设，即完全理性的代理人通过有效市场进行互动以寻求均衡，越来越不满意，这为经济学中的不同方法创造了新的激励。复杂性科学可能提供一个平台，在看似不同的领域，如脑科学和经济学，跨越学科界限。在这篇论文中，我们采取了一种综合的立场，培养了对神经活动的经济特征的新见解。这里的目标是精确地描述神经科学和经济科学中的共同主题，在一个基于经验基础的系统展望中，震撼了整个复杂系统科学的统一。认为这主要依赖于用真正的贝叶斯方法研究复杂系统的反问题。
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英文标题：
《Towards a new brain science: lessons from the economic collapse》
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作者：
Jaime Gomez-Ramirez and Manuel G. Bedia
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最新提交年份：
2012
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分类信息：
一级分类：Physics 物理学
二级分类：Adaptation and Self-Organizing Systems 自适应和自组织系统
分类描述：Adaptation, self-organizing systems, statistical physics, fluctuating systems, stochastic processes, interacting particle systems, machine learning
自适应，自组织系统，统计物理，波动系统，随机过程，相互作用粒子系统，机器学习
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一级分类：Quantitative Finance 数量金融学
二级分类：General Finance 一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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英文摘要：
Economies are complex man-made systems where organisms and markets interact according to motivations and principles not entirely understood yet. The increasing dissatisfaction with the postulates of traditional economics i.e. perfectly rational agents, interacting through efficient markets in the search of equilibrium, has created new incentives for different approaches in economics. The science of complexity may provide the platform to cross disciplinary boundaries in seemingly disparate fields such as brain science and economics. In this paper we take an integrative stance, fostering new insights into the economic character of neural activity. The objective here is to precisely delineate common topics in both neural and economic science, within a systemic outlook grounded in empirical basis that jolts the unification across the science of complex systems. It is argued that this mainly relies on the study of the inverse problem in complex system with a truly Bayesian approach.
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PDF链接：
https://arxiv.org/pdf/1205.2999
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