Authors
Fashen Li, School of Physical Science and Technology, Lanzhou University, Lanzhou 730000, China
Lian Li, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China
Jianping Yin, School of Cyber Science and Engineering, Dongguan University of Technology, Dongguan 523808, China
Liang Huang, Institute of Computational Physics and Complex Systems, Lanzhou University, Lanzhou 730000, China
Qingguo Zhou, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
Ning An, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China
Yong Zhang, Department of Physics, Xiamen University, Xiamen 361005, China
Li Liu, School of Big Data & Software Engineering, Chongqing University, Chongqing 400044, China
Jialin Zhang, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
Kun Kuang, College of Computer Science and Technology, Zhejiang University, Hangzhou 310000, China
Lei Yang, Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000, China
Zhixi Wu, Institute of Computational Physics and Complex Systems, Lanzhou University, Lanzhou 730000, China
Lianchun Yu, Institute of Computational Physics and Complex Systems, Lanzhou University, Lanzhou 730000, China
Keywords
intelligent machine, machine knowledge, human cognition, knowledge interpretation, principle of functional similarity, Probable Approximative Correction (PAC) model
Abstract
Intelligent machines are knowledge systems with unique knowledge structure and function. In this paper, we discuss issues including the characteristics and forms of machine knowledge, the relationship between knowledge and human cognition, and the approach to acquire machine knowledge. These issues are of great significance to the development of artificial intelligence.
Publisher
Tsinghua University Press
Recommended Citation
Fashen Li, Lian Li, Jianping Yin et al. Machine Knowledge and Human Cognition. Big Data Mining and Anyalytics 2020, 3(4): 292-299.
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