Phasic Diversity Optimization for Population-Based Reinforcement Learning-Reference-Cited by-同舟云学术

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Phasic Diversity Optimization for Population-Based Reinforcement Learning

Published:2024-05-13 Issue: Volume:33 Page:272-278
ISSN:
Container-title:2024 IEEE International Conference on Robotics and Automation (ICRA)
language:
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Author:

Jiang Jingcheng¹,Piao Haiyin²,Fu Yu¹,Hao Yihang³,Jiang Chuanlu¹,Wei Ziqi⁴,Yang Xin¹

Affiliation:

1. Dalian University of Technology,Key Laboratory of Social Computing and Cognitive Intelligence,Dalian,China

2. Northwestern Polytechnical University,School of Electronics and Information,Xi’an,China

3. Yangzhou Collaborative Innovation Research Institute Co., Ltd,Yangzhou,China

4. Chinese Academy of Sciences,Institute of Automation,Beijing,China

Funder

Research and Development

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10609961/10609862/10610814.pdf?arnumber=10610814

Reference35 articles.

1. Policy gradient assisted MAP-Elites

2. Diverse auto-curriculum is critical for successful real-world multiagent learning systems;Yang;AAMAS ’21,2021

3. Determinantal Point Processes for Machine Learning

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