QDAP: Downsizing adaptive policy for cooperative multi-agent reinforcement learning-Reference-Cited by-同舟云学术

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QDAP: Downsizing adaptive policy for cooperative multi-agent reinforcement learning

Published:2024-06 Issue: Volume:294 Page:111719
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Zhao Zhitong^ORCID,Zhang Ya,Wang Siying^ORCID,Zhang Fan^ORCID,Zhang Malu,Chen Wenyu^ORCID

Funder

National Natural Science Foundation of China

Sichuan Province Science and Technology Support Program

Publisher

Elsevier BV

Reference63 articles.

1. A Concise Introduction to Decentralized POMDPs;Oliehoek,2016

2. An overview of recent progress in the study of distributed multi-agent coordination;Cao;IEEE Trans. Ind. Inform.,2013

3. Auto-learning communication reinforcement learning for multi-intersection traffic light control;Zhu;Knowl.-Based Syst.,2023

4. Drone mapping through multi-agent reinforcement learning;Zanol,2019

5. Guided deep reinforcement learning for swarm systems;Hüttenrauch,2017

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. VAOS: Enhancing the stability of cooperative multi-agent policy learning;Knowledge-Based Systems;2024-11

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