Improve the performance of neural network training with accurate information: Take Connect6 for example

Shih Hao Huang, Chih Hung Chen, Shun Shii Lin*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

DeepMind introduced a general reinforcement learning algorithm called AlphaZero to learn through self-play without any human knowledge. It got a superhuman success not only in Go but also in Chess and Shogi. Nevertheless, AlphaZero needs huge computational resources to train a high quality neural network. Most institutions have no such huge computational resources or cannot invest an enormous number of resources to support a research project. Therefore, this paper proposes to embed accurate information into the training phase for improving the performance of the neural network under limited resources. In competition with Zeta-180, the win rate of FD-60 far surpasses all other modifications. The results of experiments indicate that embedding accurate information into the training-phase can effectively improve the performance of the neural network under limited resources.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Advanced Information Science and System, AISS 2019
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450372916
DOIs
Publication statusPublished - 2019 Nov 15
Event2019 International Conference on Advanced Information Science and System, AISS 2019 - Singapore, Singapore
Duration: 2019 Nov 152019 Nov 17

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2019 International Conference on Advanced Information Science and System, AISS 2019
Country/TerritorySingapore
CitySingapore
Period2019/11/152019/11/17

Keywords

  • AlphaZero
  • Connect6
  • Deep learning
  • Neural network
  • Reinforcement learning

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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