A Dynamic Approach for Handling UAV in Crowded Environment Using Deep Q-Networks-Reference-Cited by-同舟云学术

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A Dynamic Approach for Handling UAV in Crowded Environment Using Deep Q-Networks

Published:2023-10-06 Issue: Volume: Page:
ISSN:
Container-title:2023 4th IEEE Global Conference for Advancement in Technology (GCAT)
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Author:

Upadhyay Yash¹,Gahlawat Muskan²,Nivetha S.³,Rana Saurabh²,Natarajan B⁴,Gupta Pratik⁵

Affiliation:

1. Amrita School of Computing, Amrita Vishwa Vidyapeetham,Department of Computer Science and Engineering (AIE),Chennai,India,601103

2. RVS College of Engineering & Technology,Department of Computer Science and Engineering,Coimbatore,641402

3. Chandigarh University,Department of Mathematics

4. Amrita Vishwa Vidyapeetham,Department of Computer Science and Engineering (AIE),Chennai,India,601103

5. Gautam Buddha University,Department of Applied Mathematics,Noida

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10353069/10353233/10353326.pdf?arnumber=10353326

Reference34 articles.

1. Multi-Agent Deep Reinforcement Learning for Secure UAV Communications

2. Multiagent cooperation and competition with deep reinforcement learning

3. Distributed UAV-BSs Trajectory Optimization for User-Level Fair Communication Service With Multi-Agent Deep Reinforcement Learning

4. Future of healthcare start-ups in the era of digitalization: bibliometric analysis

5. Scalable and Cooperative Deep Reinforcement Learning Approaches for Multi-UAV Systems: A Systematic Review

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