Multiagent Deep Reinforcement Learning With Demonstration Cloning for Target Localization-Reference-Cited by-同舟云学术

Multiagent Deep Reinforcement Learning With Demonstration Cloning for Target Localization

Published:2023-08-01 Issue:15 Volume:10 Page:13556-13570
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Alagha Ahmed¹^ORCID,Mizouni Rabeb²^ORCID,Bentahar Jamal¹^ORCID,Otrok Hadi²^ORCID,Singh Shakti²^ORCID

Affiliation:

1. Concordia Institute for Information Systems Engineering, Concordia University, Montreal, QC, Canada

2. Department of Electrical Engineering and Computer Science and the Center of Cyber Physical Systems, Khalifa University, Abu Dhabi, UAE

Funder

Fonds de Recherche du Québec—Nature et Technologies

Natural Sciences and Engineering Research Council of Canada

Department of National Defense [Innovation for Defence Excellence and Security (IDEaS)]

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/10194321/10083192.pdf?arnumber=10083192

Reference39 articles.

1. Contrasting centralized and decentralized critics in multi-agent reinforcement learning;lyu;Proc 20th Int Conf Auton Agents MultiAgent Syst (AAMAS),2021

2. The Lost Source, Varying Backgrounds and Why Bigger May Not Be Better

3. Emergent tool use from multi-agent autocurricula;baker;Proc Int Conf Learn Rep (ICLR),2020

4. A Sampling-Based Bayesian Approach for Cooperative Multiagent Online Search With Resource Constraints

5. Overcoming Exploration in Reinforcement Learning with Demonstrations

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