• DOI:10.1109/ACCESS.2019.2938568
Corpus ID: 202560795

Improved Online Sequential Extreme Learning Machine: A New Intelligent Evaluation Method for AZ-Style Algorithms

@article{Li2019ImprovedOS,
  title={Improved Online Sequential Extreme Learning Machine: A New Intelligent Evaluation Method for AZ-Style Algorithms},
  author={X. Li and S. He and Z. Wei and Licheng Wu},
  journal={IEEE Access},
  year={2019},
  volume={7},
  pages={124891-124901}
}

X. Li, S. He, +1 author Licheng Wu

Published 2019

Computer Science

IEEE Access

Researches on computer games for Go, Chess, and Japanese Chess stand out as one of the notable landmarks in the progress of artificial intelligence. AlphaGo, AlphaGo Zero, and AlphaZero algorithms, which are called AlphaZero style (AZ-style) algorithms in some literature [1], have achieved superhuman performance by using deep reinforcement learning (DRL). However, the unavailability of training details, expensive equipment used for model training, and the low evaluation accuracy resulted by… CONTINUE READING

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