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摘要翻译：
什么是信息？是身体上的吗？我们认为，在贝叶斯理论中，信息的概念必须根据它对理性主体信念的影响来定义。信息是限制理性信念的任何东西，因此它是诱使我们改变思想的力量。从先验概率分布到后验概率分布的更新问题是通过一个排除归纳法来解决的，该归纳法将对数相对熵作为唯一的推理工具。由此产生的最大相对熵(ME)方法是针对以任意约束形式对给定信息进行更新的任意先验信息而设计的，它包括MaxEnt（允许任意约束）和Bayes（允许任意先验）两种特例。因此，ME将这些研讨会的两个主题--最大熵和贝叶斯方法--统一到一个单一的通用推理方案中，使我们能够分别处理两种方法中任何一种无法解决的问题。我以几个简单的示例来结束。
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英文标题：
《Information and Entropy》
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作者：
Ariel Caticha
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最新提交年份：
2007
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分类信息：
一级分类：Physics 物理学
二级分类：Data Analysis, Statistics and Probability 数据分析、统计与概率
分类描述：Methods, software and hardware for physics data analysis: data processing and storage; measurement methodology; statistical and mathematical aspects such as parametrization and uncertainties.
物理数据分析的方法、软硬件：数据处理与存储；测量方法；统计和数学方面，如参数化和不确定性。
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一级分类：Physics 物理学
二级分类：Statistical Mechanics 统计力学
分类描述：Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变，热力学，场论，非平衡现象，重整化群和标度，可积模型，湍流
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一级分类：Physics 物理学
二级分类：General Relativity and Quantum Cosmology 广义相对论与量子宇宙学
分类描述：General Relativity and Quantum Cosmology Areas of gravitational physics, including experiments and observations related to the detection and interpretation of gravitational waves, experimental tests of gravitational theories, computational general relativity, relativistic astrophysics, solutions to Einstein's equations and their properties, alternative theories of gravity, classical and quantum cosmology, and quantum gravity.
广义相对论和量子宇宙学引力物理领域，包括与探测和解释引力波有关的实验和观测、引力理论的实验检验、计算广义相对论、相对论天体物理学、爱因斯坦方程及其性质的解、引力的替代理论、经典宇宙学和量子宇宙学以及量子引力。
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一级分类：Mathematics 数学
二级分类：Statistics Theory 统计理论
分类描述：Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计：例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
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一级分类：Physics 物理学
二级分类：General Physics 普通物理学
分类描述：Description coming soon
描述即将到来
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一级分类：Statistics 统计学
二级分类：Statistics Theory 统计理论
分类描述：stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近，贝叶斯推论，决策理论，估计，基础，推论，检验。
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英文摘要：
What is information? Is it physical? We argue that in a Bayesian theory the notion of information must be defined in terms of its effects on the beliefs of rational agents. Information is whatever constrains rational beliefs and therefore it is the force that induces us to change our minds. This problem of updating from a prior to a posterior probability distribution is tackled through an eliminative induction process that singles out the logarithmic relative entropy as the unique tool for inference. The resulting method of Maximum relative Entropy (ME), which is designed for updating from arbitrary priors given information in the form of arbitrary constraints, includes as special cases both MaxEnt (which allows arbitrary constraints) and Bayes' rule (which allows arbitrary priors). Thus, ME unifies the two themes of these workshops -- the Maximum Entropy and the Bayesian methods -- into a single general inference scheme that allows us to handle problems that lie beyond the reach of either of the two methods separately. I conclude with a couple of simple illustrative examples.
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PDF链接：
https://arxiv.org/pdf/710.1068
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