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A geospatial service composition approach based on MCTS with temporal-difference learning

Zhuang Can Guo Mingqiang Xie Zhong

高技术通讯（英文版）2021，Vol.27Issue(1)：17-25,9.

高技术通讯（英文版）2021，Vol.27Issue(1)：17-25,9.DOI:10.3772/j.issn.1006-6748.2021.01.003

A geospatial service composition approach based on MCTS with temporal-difference learning

Zhuang Can ¹Guo Mingqiang ¹Xie Zhong¹

作者信息

1. School of Geography and Information Engineering,China University of Geosciences,Wuhan 430074,P.R.China
折叠

摘要

关键词

geospatial service composition/reinforcement learning(RL)/Markov decision process(MDP)/Monte Carlo tree search(MCTS)/temporal-difference(TD)learning

Key words

geospatial service composition/reinforcement learning(RL)/Markov decision process(MDP)/Monte Carlo tree search(MCTS)/temporal-difference(TD)learning

引用本文复制引用

Zhuang Can,Guo Mingqiang,Xie Zhong..A geospatial service composition approach based on MCTS with temporal-difference learning[J].高技术通讯（英文版）,2021,27(1):17-25,9.

基金项目

Supported by the National Natural Science Foundation of China(No.41971356,41671400,41701446),National Key Research and Development Program of China(No.2017YFB0503600,2018YFB0505500),and Hubei Province Natural Science Foundation of China(No.2017CFB277). （No.41971356,41671400,41701446）

高技术通讯（英文版）

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ISSN：1006-6748

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