摘要翻译：
人们用他们的知识来认识事物。本文研究的是如何测量人们的知识以供识别，以及它是如何变化的。讨论基于三个假设。首先，我们构造了两个演化过程方程，一个是不确定性和知识的演化过程方程，另一个是不确定性和无知的演化过程方程。其次，通过求解方程组，得到了两种特殊情况下知识水平和无知水平的度量公式。第三，引入了知识熵的新概念。考察了它与玻尔兹曼熵的相似性和与香农熵的区别。最后指出，所得到的知识和知识熵公式反映了两个基本原理：（1）群体的知识水平不一定是个体知识水平的简单总和；并且（2）如果一个人的求知欲从不降低，那么他的知识熵从不增加。
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英文标题：
《Measuring Knowledge for Recognition and Knowledge Entropy》
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作者：
Fujun Hou
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最新提交年份：
2018
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分类信息：

一级分类：Economics        经济学
二级分类：Theoretical Economics        理论经济学
分类描述：Includes theoretical contributions to Contract Theory, Decision Theory, Game Theory, General Equilibrium, Growth, Learning and Evolution, Macroeconomics, Market and Mechanism Design, and Social Choice.
包括对契约理论、决策理论、博弈论、一般均衡、增长、学习与进化、宏观经济学、市场与机制设计、社会选择的理论贡献。
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英文摘要：
  People employ their knowledge to recognize things. This paper is concerned with how to measure people's knowledge for recognition and how it changes. The discussion is based on three assumptions. Firstly, we construct two evolution process equations, of which one is for uncertainty and knowledge, and the other for uncertainty and ignorance. Secondly, by solving the equations, formulas for measuring the levels of knowledge and the levels of ignorance are obtained in two particular cases. Thirdly, a new concept of knowledge entropy is introduced. Its similarity with Boltzmann's entropy and its difference with Shannon's Entropy are examined. Finally, it is pointed out that the obtained formulas of knowledge and knowledge entropy reflect two fundamental principles: (1) The knowledge level of a group is not necessarily a simple sum of the individuals' knowledge levels; and (2) An individual's knowledge entropy never increases if the individual's thirst for knowledge never decreases.
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PDF链接：
https://arxiv.org/pdf/1811.06135