Graded-Q Reinforcement Learning with Information-Enhanced State Encoder for Hierarchical Collaborative Multi-Vehicle Pursuit-Reference-Cited by-同舟云学术

Graded-Q Reinforcement Learning with Information-Enhanced State Encoder for Hierarchical Collaborative Multi-Vehicle Pursuit

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 18th International Conference on Mobility, Sensing and Networking (MSN)
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Author:

Yang Yiying¹,Li Xinhang¹,Yuan Zheng¹,Wang Qinwen¹,Xu Chen¹,Zhang Lin¹

Affiliation:

1. School of Artificial Intelligence, Beijing University of Posts and Telecommunications,Beijing,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10076543/10076544/10076677.pdf?arnumber=10076677

Reference16 articles.

1. Game of Drones: Multi-UAV Pursuit-Evasion Game With Online Motion Planning by Deep Reinforcement Learning

2. A Novel Method Combining Leader-Following Control and Reinforcement Learning for Pursuit Evasion Games of Multi-Agent Systems

3. Modeling the interaction between agents in cooperative multi-agent reinforcement learning;ma;Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems AAMAS '21,2021

4. T3OMVP: A Transformer-Based Time and Team Reinforcement Learning Scheme for Observation-Constrained Multi-Vehicle Pursuit in Urban Area

5. Coach-player multi-agent reinforcement learning for dynamic team composition;liu;International Conference on Machine Learning,2021

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