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Multi-Agent Deep Reinforcement Learning For Persistent Monitoring With Sensing, Communication, and Localization Constraints

Multi-Agent Deep Reinforcement Learning For Persistent Monitoring With Sensing, Communication, and Localization Constraints

M. Mishra
Prithvi Poddar
Rajat Agrawal
Jingxi Chen
Pratap Tokekar
P. B. Sujit
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Papers citing "Multi-Agent Deep Reinforcement Learning For Persistent Monitoring With Sensing, Communication, and Localization Constraints"

4 / 4 papers shown
Title
The Emergence of Adversarial Communication in Multi-Agent Reinforcement Learning
The Emergence of Adversarial Communication in Multi-Agent Reinforcement Learning
J. Blumenkamp
Amanda Prorok
AAML
AI4CE
33
59
0
06 Aug 2020
Mobile Robot Path Planning in Dynamic Environments through Globally Guided Reinforcement Learning
Mobile Robot Path Planning in Dynamic Environments through Globally Guided Reinforcement Learning
Binyu Wang
Zhe Liu
Qingbiao Li
Amanda Prorok
40
225
0
11 May 2020
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability
Shayegan Omidshafiei
Jason Pazis
Chris Amato
Jonathan P. How
J. Vian
82
497
0
17 Mar 2017
Persistent Monitoring of Events with Stochastic Arrivals at Multiple Stations
Persistent Monitoring of Events with Stochastic Arrivals at Multiple Stations
Jingjin Yu
S. Karaman
Daniela Rus
36
69
0
24 Sep 2013