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Deep Reinforcement Learning for Autonomous Driving: A Survey

IEEE transactions on intelligent transportation systems, 2022-06, Vol.23 (6), p.4909-4926

2022

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Multi-Agent Deep Reinforcement Learning for Large-Scale Traffic Signal Control

IEEE transactions on intelligent transportation systems, 2020-03, Vol.21 (3), p.1086-1095

2020

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Hierarchical Reinforcement Learning: A Comprehensive Survey

ACM computing surveys, 2021-06, Vol.54 (5), p.1-35

2021

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Single and Multi-Agent Deep Reinforcement Learning for AI-Enabled Wireless Networks: A Tutorial

IEEE Communications surveys and tutorials, 2021-01, Vol.23 (2), p.1226-1252

2021

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Challenges of real-world reinforcement learning: definitions, benchmarks and analysis

Machine learning, 2021-09, Vol.110 (9), p.2419-2468

2021

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Safe Off-Policy Deep Reinforcement Learning Algorithm for Volt-VAR Control in Power Distribution Systems

IEEE transactions on smart grid, 2020-07, Vol.11 (4), p.3008-3018

2020

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Multi-Agent Reinforcement Learning based Uplink OFDMA for IEEE 802.11ax Networks

IEEE transactions on wireless communications, 2024, p.1-1

2024

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GAN-Powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing

IEEE journal on selected areas in communications, 2020-02, Vol.38 (2), p.334-349

2020

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Volltext

Applications of Deep Reinforcement Learning in Communications and Networking: A Survey

IEEE Communications surveys and tutorials, 2019-01, Vol.21 (4), p.3133-3174

2019

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Deep clustering of cooperative multi-agent reinforcement learning to optimize multi chiller HVAC systems for smart buildings energy management

Journal of Building Engineering, 2023-04, Vol.65, p.105689, Article 105689

2023

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Nash double Q-based multi-agent deep reinforcement learning for interactive merging strategy in mixed traffic

Expert systems with applications, 2024-03, Vol.237, p.121458, Article 121458

2024

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Multi-Agent Reinforcement Learning-Based Resource Allocation for UAV Networks

IEEE transactions on wireless communications, 2020-02, Vol.19 (2), p.729-743

2020

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Reinforcement Learning and Its Applications in Modern Power and Energy Systems: A Review

Journal of modern power systems and clean energy, 2020-11, Vol.8 (6), p.1029-1042

2020

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Maintenance optimisation of multicomponent systems using hierarchical coordinated reinforcement learning

Reliability engineering & system safety, 2022-01, Vol.217, p.108078, Article 108078

2022

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Semisupervised Deep Reinforcement Learning in Support of IoT and Smart City Services

IEEE internet of things journal, 2018-04, Vol.5 (2), p.624-635

2018

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A Tutorial on Ultrareliable and Low-Latency Communications in 6G: Integrating Domain Knowledge Into Deep Learning

Proceedings of the IEEE, 2021-03, Vol.109 (3), p.204-246

2021

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Federated Reinforcement Learning for Energy Management of Multiple Smart Homes With Distributed Energy Resources

IEEE transactions on industrial informatics, 2022-01, Vol.18 (1), p.488-497

2022

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Volltext

Deep Reinforcement Learning-Based Intelligent Reflecting Surface for Secure Wireless Communications

IEEE transactions on wireless communications, 2021-01, Vol.20 (1), p.375-388

2021

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A survey and critique of multiagent deep reinforcement learning

Autonomous agents and multi-agent systems, 2019-11, Vol.33 (6), p.750-797

2019

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Deep Reinforcement Learning Based Resource Allocation for V2V Communications

IEEE transactions on vehicular technology, 2019-04, Vol.68 (4), p.3163-3173

2019

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Teacher-Student Curriculum Learning

IEEE transaction on neural networks and learning systems, 2020-09, Vol.31 (9), p.3732-3740

2020

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Interference Management for Cellular-Connected UAVs: A Deep Reinforcement Learning Approach

IEEE transactions on wireless communications, 2019-04, Vol.18 (4), p.2125-2140

2019

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Volltext

Deep Reinforcement Learning for Multiagent Systems: A Review of Challenges, Solutions, and Applications

IEEE transactions on cybernetics, 2020-09, Vol.50 (9), p.3826-3839

2020

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Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning

IEEE transaction on neural networks and learning systems, 2019-11, Vol.30 (11), p.3409-3418

2019

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Spectrum Sharing in Vehicular Networks Based on Multi-Agent Reinforcement Learning

IEEE journal on selected areas in communications, 2019-10, Vol.37 (10), p.2282-2292

2019

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Deep Reinforcement Learning for Autonomous Driving: A Survey

Multi-Agent Deep Reinforcement Learning for Large-Scale Traffic Signal Control

Hierarchical Reinforcement Learning: A Comprehensive Survey

Single and Multi-Agent Deep Reinforcement Learning for AI-Enabled Wireless Networks: A Tutorial

Challenges of real-world reinforcement learning: definitions, benchmarks and analysis

Safe Off-Policy Deep Reinforcement Learning Algorithm for Volt-VAR Control in Power Distribution Systems

Multi-Agent Reinforcement Learning based Uplink OFDMA for IEEE 802.11ax Networks

GAN-Powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing

Applications of Deep Reinforcement Learning in Communications and Networking: A Survey

Deep clustering of cooperative multi-agent reinforcement learning to optimize multi chiller HVAC systems for smart buildings energy management

Nash double Q-based multi-agent deep reinforcement learning for interactive merging strategy in mixed traffic

Multi-Agent Reinforcement Learning-Based Resource Allocation for UAV Networks

Reinforcement Learning and Its Applications in Modern Power and Energy Systems: A Review

Maintenance optimisation of multicomponent systems using hierarchical coordinated reinforcement learning

Semisupervised Deep Reinforcement Learning in Support of IoT and Smart City Services

A Tutorial on Ultrareliable and Low-Latency Communications in 6G: Integrating Domain Knowledge Into Deep Learning

Federated Reinforcement Learning for Energy Management of Multiple Smart Homes With Distributed Energy Resources

Deep Reinforcement Learning-Based Intelligent Reflecting Surface for Secure Wireless Communications

A survey and critique of multiagent deep reinforcement learning

Deep Reinforcement Learning Based Resource Allocation for V2V Communications

Teacher-Student Curriculum Learning

Interference Management for Cellular-Connected UAVs: A Deep Reinforcement Learning Approach

Deep Reinforcement Learning for Multiagent Systems: A Review of Challenges, Solutions, and Applications

Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning

Spectrum Sharing in Vehicular Networks Based on Multi-Agent Reinforcement Learning

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