Deep Q-Learning to Preserve Connectivity in Multi-robot Systems-Reference-Cited by-同舟云学术

Deep Q-Learning to Preserve Connectivity in Multi-robot Systems

Published:2017 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 9th International Conference on Signal Processing Systems - ICSPS 2017
language:
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Author:

Huang Wanrong¹,Wang Yanzhen¹,Yi Xiaodong¹

Affiliation:

1. College of Computer, National University of Defense Technology, Changsha, Hunan, P.R. China

Funder

Research on Foundations of Major Applications, Research Programs of NUDT

National Science Foundation of China

Publisher

ACM Press

Reference19 articles.

1. Tang M, Zhu H, Mao X: A Lightweight Social Computing Approach to Emergency Management Policy Selection[J]. IEEE Transactions on Systems Man & Cybernetics Systems, 1(1-2):1--13 (2015).

2. Tang M, Mao X, Guessoum Z: Research on an infectious disease transmission by flocking birds[J]. Scientific World Journal, 2013(12):196823 (2013).

3. Wu, Yunlong, et al: Communication-Motion Planning for Wireless RelayAssisted Multi-Robot System. IEEE Wireless Communications Letters 5.6(2016):568--571.

4. Wen, G., et al: A connectivity-preserving flocking algorithm for multiagent dynamical systems with bounded potential function. Control Theory and Applications Iet 6.6(2012):813--821.

5. Mehta, Vaibhav Kumar, and F. Arrichiello: Connectivity maintenance by robotic Mobile Ad-hoc NETwork. Computer Science (2013).

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