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Balance Rule in Artificial Intelligence

  • Wenwei LiEmail author
  • Guangsheng LuoEmail author
  • Fei DaiEmail author
  • Rong LiEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1072)

Abstract

Deep learning embodied some essence of artificial intelligence, but it relied on data set and lacked migration learning ability. We should build general theorem to explain artificial intelligence from nature or human. We can treat each static data as a variable like wave-particle duality, then we can adopt idea from convolutional neural network or other machine learning algorithms to extract features from little data. This method can open up a new theory to accomplish migration learning and artificial intelligence. The theory will be supported by balance rule: everything has a gradient and tends to remain a zero gradient state, and we can connect different feature spaces by gradients.

Keywords

Artificial intelligence Wave-particle duality Balance rule 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Fudan UniversityShanghaiChina
  2. 2.Wuhan UniversityWuhanChina
  3. 3.Hubei University of MedicineShiyanChina

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