| الملخص: | Automated deep learning is one of the new research hotspots in the field of deep learning.Neural architecture search algorithms are frequently used for the implementation of automated deep learning,as they can automatically design neural network structure by defining different search space,search strategy or optimization strategy.This paper introduces the development history of evolutionary algorithms and evolutionary neural networks.Then it introduces different methods and processes of using evolutionary algorithms as the search strategy to implement neural architecture search,and compares the features and development status of these neural architecture search algorithms.On this basis,this paper discusses the search space,search strategy and future development direction of neural architecture search algorithms.
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