Open AccessStudy on the Learning Algorithms of Artificial Intelligence
Author(s) -
Qinghua Sun,
Fang Yin
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/440/5/052046
Subject(s) - artificial intelligence , computer science , artificial neural network , algorithm , field (mathematics) , machine learning , artificial intelligence system , artificial intelligence, situated approach , set (abstract data type) , marketing and artificial intelligence , process (computing) , intelligent decision support system , mathematics , pure mathematics , programming language , operating system
This article delves into artificial intelligence algorithms. From a functional and formal point of view, the artificial intelligence algorithms are divided into four categories which named: statistical based algorithms, tree-based algorithms, neural network-based algorithms, and comprehensive algorithms. On this basis, the common algorithm model and its principle in the field of artificial intelligence are analyzed in this paper. In order to further study the semantic logic in artificial intelligence field, based on the tools of semantic vector space model, this paper abstract and analyze the process of understanding “Knowledge Set” on the empirical level and “Control Knowledge Set” on the thinking level. This paper lays a theoretical foundation for the research of artificial intelligence and robots.