A TD3-based multi-agent deep reinforcement learning method in mixed cooperation-competition environment
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.05.097
Abstract: Abstract We explored the problem about function approximation error and complex mission adaptability in multi-agent deep reinforcement learning. This paper proposes a new multi-agent deep reinforcement learning algorithm framework named multi-agent time delayed deep deterministic… read more here.
Keywords: agent deep; reinforcement learning; deep reinforcement; multi agent ... See more keywords
Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-15982-x
Abstract: In highly dynamic vehicular networking scenarios, when Vehicle-to-Infrastructure links and Vehicle-to-Vehicle links share spectrum resources, the traditional distributed resource allocation method lacks global optimization and fails to respond to environmental changes in a timely manner,… read more here.
Keywords: agent deep; allocation method; multi agent; allocation ... See more keywords
Multi-Agent Deep Reinforcement Learning-Based Cooperative Spectrum Sensing With Upper Confidence Bound Exploration
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2937108
Abstract: In this paper, a multi-agent deep reinforcement learning method was adopted to realize cooperative spectrum sensing in cognitive radio networks. Each secondary user learns an efficient sensing strategy from the sensing results of some of… read more here.
Keywords: agent deep; reinforcement learning; reinforcement; multi agent ... See more keywords
Priority-Aware Multi-Agent Deep Reinforcement Learning for Resource Scheduling in C-V2X Mode 4 Communication
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3586804
Abstract: The need for vehicular networks with exceptional levels of reliability and negligible delay in communication, especially with the ongoing 5G and the upcoming generation of 6G systems, has given rise to Cellular-Vehicle-to-Anything C-V2X systems. This… read more here.
Keywords: agent deep; aware multi; multi agent; communication ... See more keywords
QoI-Aware Mobile Crowdsensing for Metaverse by Multi-Agent Deep Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Journal on Selected Areas in Communications"
DOI: 10.1109/jsac.2023.3345395
Abstract: Metaverse is expected to provide mobile users with emerging applications both in regular situation like intelligent transportation services and in emergencies like wireless search and disaster response. These applications are usually associated with stringent quality-of-information… read more here.
Keywords: agent deep; mobile crowdsensing; multi agent; aware mobile ... See more keywords
Multi-Agent Deep Reinforcement Learning-Based Trajectory Planning for Multi-UAV Assisted Mobile Edge Computing
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Cognitive Communications and Networking"
DOI: 10.1109/tccn.2020.3027695
Abstract: An unmanned aerial vehicle (UAV)-aided mobile edge computing (MEC) framework is proposed, where several UAVs having different trajectories fly over the target area and support the user equipments (UEs) on the ground. We aim to… read more here.
Keywords: agent deep; uav; multi agent; trajectory ... See more keywords
Cellular UAV-to-Device Communications: Trajectory Design and Mode Selection by Multi-Agent Deep Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Communications"
DOI: 10.1109/tcomm.2020.2986289
Abstract: In the current unmanned aircraft systems (UASs) for sensing services, unmanned aerial vehicles (UAVs) transmit their sensory data to terrestrial mobile devices over the unlicensed spectrum. However, the interference from surrounding terminals is uncontrollable due… read more here.
Keywords: agent deep; multi agent; uav device; deep reinforcement ... See more keywords
Multi-Agent Deep Reinforcement Learning Based Transmission Latency Minimization for Delay-Sensitive Cognitive Satellite-UAV Networks
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Communications"
DOI: 10.1109/tcomm.2022.3222460
Abstract: With the ubiquitous deployment of a massive number of Internet-of-Things (IoT) devices, the satellite-aerial networks are becoming a promising candidate to provide flexible and seamless service for IoT applications. Concerning about the spectrum scarcity issue,… read more here.
Keywords: delay sensitive; satellite; cognitive satellite; transmission latency ... See more keywords
Cooperative Multi-UAV Positioning for Aerial Internet Service Management: A Multi-Agent Deep Reinforcement Learning Approach
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Network and Service Management"
DOI: 10.1109/tnsm.2024.3392393
Abstract: This paper proposes a novel multi-agent deep reinforcement learning (MADRL)-based positioning algorithm for multiple unmanned aerial vehicles (UAVs) collaboration in mobile access applications where the UAVs work as mobile base stations. The primary objective of… read more here.
Keywords: agent deep; multi; multi agent; service ... See more keywords
O-DQR: A Multi-Agent Deep Reinforcement Learning for Multihop Routing in Overlay Networks
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Network and Service Management"
DOI: 10.1109/tnsm.2024.3485196
Abstract: This paper addresses the problem of dynamic packet routing in overlay networks using a fully decentralized Multi-Agent Deep Reinforcement Learning (MA-DRL). Overlay networks are built by having a virtual topology on top of an Internet… read more here.
Keywords: agent deep; routing overlay; overlay; multi agent ... See more keywords
UAV-Enabled Secure Communications by Multi-Agent Deep Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2020.3014788
Abstract: Unmanned aerial vehicles (UAVs) can be employed as aerial base stations to support communication for the ground users (GUs). However, the aerial-to-ground (A2G) channel link is dominated by line-of-sight (LoS) due to the high flying… read more here.
Keywords: secure; agent deep; reinforcement learning; multi agent ... See more keywords