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第15行： + − 自我组织的生物系统——比如细胞或大脑——可以被理解为最小化变分自由能的概念，是基于亥姆霍兹在无意识推理<ref name="Helmholtz">Helmholtz, H. (1866/1962). Concerning the perceptions in general. In Treatise on physiological optics (J. Southall, Trans., 3rd ed., Vol. III). New York: Dover.</ref>以及随后的心理学<ref>{{cite journal | title=Perceptions as hypotheses | journal=Philosophical Transactions of the Royal Society of London. B, Biological Sciences | publisher=The Royal Society | volume=290 | issue=1038 | date=1980-07-08 | issn=0080-4622 | doi=10.1098/rstb.1980.0090 | pmid=6106237 | bibcode=1980RSPTB.290..181G | pages=181–197|jstor=2395424| last1=Gregory | first1=R. L. | doi-access=free }}</ref>和机器学习<ref name="Dayan">{{cite journal | last1=Dayan | first1=Peter | last2=Hinton | first2=Geoffrey E. | last3=Neal | first3=Radford M. | last4=Zemel | first4=Richard S. | title=The Helmholtz Machine | journal=Neural Computation | publisher=MIT Press - Journals | volume=7 | issue=5 | year=1995 | issn=0899-7667 | doi=10.1162/neco.1995.7.5.889 | pmid=7584891 | pages=889–904| s2cid=1890561 |url=http://www.gatsby.ucl.ac.uk/~dayan/papers/hm95.pdf}}</ref>治疗方面的工作。变分自由能是观测值及其隐含原因的概率密度的函数。这个变分密度的定义关系到一个概率模型，从假设的原因产生预测观测。在这种情况下，自由能提供了一个近似贝叶斯模型<ref>Beal, M. J. (2003). [http://www.cse.buffalo.edu/faculty/mbeal/papers/beal03.pdf Variational Algorithms for Approximate Bayesian Inference]. Ph.D. Thesis, University College London.</ref>的证据。因此，它的最小化可以被看作是一个贝叶斯推断过程。当一个系统积极地进行观测以最小化自由能时，它隐含地进行了积极推理并最大化其世界模型的证据。+ 第32行：
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无编辑摘要
== 背景==
== 背景==
The notion that self-organising biological systems – like a cell or brain – can be understood as minimising variational free energy is based upon Helmholtz’s work on unconscious inference and subsequent treatments in psychology and machine learning. Variational free energy is a function of observations and a probability density over their hidden causes. This variational density is defined in relation to a probabilistic model that generates predicted observations from hypothesized causes. In this setting, free energy provides an approximation to Bayesian model evidence. Therefore, its minimisation can be seen as a Bayesian inference process. When a system actively makes observations to minimise free energy, it implicitly performs active inference and maximises the evidence for its model of the world.
自我组织的生物系统——比如细胞或大脑——可以被理解为最小化变分自由能的概念，是基于亥姆霍兹在无意识推理以及随后的心理学和机器学习治疗方面的工作。变分自由能是观测值及其隐含原因的概率密度的函数。这个变分密度的定义关系到一个概率模型，从假设的原因产生预测观测。在这种情况下，自由能提供了一个近似贝叶斯模型的证据。因此，它的最小化可以被看作是一个贝叶斯推断过程。当一个系统积极地进行观测以最小化自由能时，它隐含地进行了积极推理并最大化其世界模型的证据。
=== 与其他理论的关系===
=== Relationship to other theories 与其他理论的关系===
Active inference is closely related to the good regulator theorem and related accounts of self-organisation, such as self-assembly, pattern formation, autopoiesis and practopoiesis. It addresses the themes considered in cybernetics, synergetics and embodied cognition. Because free energy can be expressed as the expected energy of observations under the variational density minus its entropy, it is also related to the maximum entropy principle. Finally, because the time average of energy is action, the principle of minimum variational free energy is a principle of least action.
Active inference is closely related to the good regulator theorem and related accounts of self-organisation, such as self-assembly, pattern formation, autopoiesis and practopoiesis. It addresses the themes considered in cybernetics, synergetics and embodied cognition. Because free energy can be expressed as the expected energy of observations under the variational density minus its entropy, it is also related to the maximum entropy principle. Finally, because the time average of energy is action, the principle of minimum variational free energy is a principle of least action.
这些示意图说明了如何将状态划分为内部状态和隐藏状态或外部状态，这些状态由一个马尔可夫毯（包括感觉状态和活动状态）分隔开来。下面的面板显示了这个分区，因为它将应用于大脑中的动作和感知；活动和内部状态将感官状态的自由能功能最小化。随后内部状态的自组织与感知相对应，而动作将大脑状态与外部状态耦合。上面的面板显示完全相同的依赖性，但重新排列，使内部状态与细胞内状态相关联，而感觉状态成为细胞膜的表面状态覆盖活性状态（例如，细胞骨架的肌动蛋白丝）。
这些示意图说明了如何将状态划分为内部状态和隐藏状态或外部状态，这些状态由一个马尔可夫毯（包括感觉状态和活动状态）分隔开来。下面的面板显示了这个分区，因为它将应用于大脑中的动作和感知；活动和内部状态将感官状态的自由能功能最小化。随后内部状态的自组织与感知相对应，而动作将大脑状态与外部状态耦合。上面的面板显示完全相同的依赖性，但重新排列，使内部状态与细胞内状态相关联，而感觉状态成为细胞膜的表面状态覆盖活性状态（例如，细胞骨架的肌动蛋白丝）。
== 定义 ==
== Definition定义 ==