Privacy-Engineered Value Decomposition Networks for Cooperative Multi-Agent Reinforcement Learning-Reference-Cited by-同舟云学术

Privacy-Engineered Value Decomposition Networks for Cooperative Multi-Agent Reinforcement Learning

Published:2023-12-13 Issue: Volume: Page:8038-8044
ISSN:
Container-title:2023 62nd IEEE Conference on Decision and Control (CDC)
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Author:

Gohari Parham¹,Hale Matthew²,Topcu Ufuk³

Affiliation:

1. Robert Strauss Center for International Security and Law, University of Texas at Austin,The Department of Electrical and Computer Engineering,Austin,TX,USA

2. University of Florida,The Faculty of Mechanical and Aerospace Engineering,Gainesville,FL,USA

3. University of Texas at Austin,Faculty of Aerospace Engineering and Engineering Mechanics,Austin,TX,USA

Funder

AFOSR

ONR

AFRL

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10383192/10383193/10384184.pdf?arnumber=10384184

Reference30 articles.

1. Deep Learning with Differential Privacy

2. Survey of Deep Reinforcement Learning for Motion Planning of Autonomous Vehicles

3. Relevant Experiences in Replay Buffer

4. Information Flow and Cooperative Control of Vehicle Formations

5. Privacy-Engineered Value Decomposition Networks for Cooperative Multi-Agent Reinforcement Learning

Cited by 2 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. Survey of Recent Results in Privacy-Preserving Mechanisms for Multi-Agent Systems;Journal of Intelligent & Robotic Systems;2024-09-05

2. Privacy-Engineered Value Decomposition Networks for Cooperative Multi-Agent Reinforcement Learning;2023 62nd IEEE Conference on Decision and Control (CDC);2023-12-13