Surrogate-Assisted Evolutionary Q-Learning for Black-Box Dynamic Time-Linkage Optimization Problems-Reference-Cited by-同舟云学术

Surrogate-Assisted Evolutionary Q-Learning for Black-Box Dynamic Time-Linkage Optimization Problems

Published:2022 Issue: Volume: Page:1-1
ISSN:1089-778X
Container-title:IEEE Transactions on Evolutionary Computation
language:
Short-container-title:IEEE Trans. Evol. Computat.

Author:

Zhang Tuo¹,Wang Handing¹,Yuan Bo²,Jin Yaochu³,Yao Xin²

Affiliation:

1. School of Artificial Intelligence and the Collaborative Innovation Center of Quantum Information of Shaanxi Province, Xidian University, Xi’an 710071, China.

2. Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, Southern University of Science and Technology, Shenzhen 518055, China.

3. Chair of Nature Inspired Computing and Engineering, Faculty of Technology, Bielefeld University, D-33615 Bielefeld, Germany.

Funder

National Natural Science Foundation of China

Guangdong Provincial Key Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Theoretical Computer Science,Software

Link

http://xplorestaging.ieee.org/ielx7/4235/4358751/09785637.pdf?arnumber=9785637

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