[1]CUI Tiejun,LI Shasha.Sample selection strategy of artificial intelligence based on factor space[J].CAAI Transactions on Intelligent Systems,2021,16(2):346-352.[doi:10.11992/tis.202003002]
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Sample selection strategy of artificial intelligence based on factor space

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 16 Number of periods: 2021 2 Page number: 346-352 Column: 学术论文—人工智能基础 Public date: 2021-03-05
Title:
Sample selection strategy of artificial intelligence based on factor space
Author(s):
CUI Tiejun1;  LI Shasha2
1. College of Safety Science and Engineering, Liaoning Technical University, Fuxin 123000, China;
2. School of business administration, Liaoning Technical University, Huludao 125105, China
Keywords:
intelligent science; factor space; Moravec’s paradox; sample selection; strategy research; factor driven; strategic network; human thinking
CLC:
TP391;X913;C931.1
DOI:
10.11992/tis.202003002
Abstract:
To solve Moravec’s paradox in artificial intelligence, in this paper, we propose a sample selection strategy based on the factor space. First, we confirm the existence of Moravec’s paradox in the factor space. Then, we determine that the process of human selection is one of comparison. It is considered that human beings must choose samples three times, i.e., they must select suitable factors, a factor concept, and a factor quantification. In the sample space, the number of samples is gradually reduced and finally each is unique after three selection rounds. Finally, to apply this strategy, the research object is divided, and a selection strategy hierarchy is established, thereby establishing the artificial-intelligence sample-selection-strategy network model. Case analysis shows that the actions taken in this process are basically factor and factor-phase operations, in which small amounts of phase measurement and data calculation are involved. This strategy is not only the sample selection process used by human beings, but is also that used by artificial intelligence.
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