Personalized federated reinforcement learning: Balancing personalization and experience sharing via distance constraint-Reference-Cited by-同舟云学术

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Personalized federated reinforcement learning: Balancing personalization and experience sharing via distance constraint

Published:2024-03 Issue: Volume:238 Page:122290
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Xiong Weicheng^ORCID,Liu Quan^ORCID,Li Fanzhang^ORCID,Wang Bangjun^ORCID,Zhu Fei^ORCID

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference39 articles.

1. Survey of deep reinforcement learning for motion planning of autonomous vehicles;Aradi;IEEE Transactions on Intelligent Transportation Systems,2022

2. Dynamic programming;Bellman;Science,1958

3. Dynamic programming and optimal control;Bertsekas,2011

4. Openai gym;Brockman,2016

5. Exploiting shared representations for personalized federated learning;Collins,2021

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. FedSAR for Heterogeneous Federated learning：A Client Selection Algorithm Based on SARSA;Lecture Notes in Computer Science;2024

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