Ga DRL

Ga DRL (Graph-Augmented Deep Reinforcement Learning) research focuses on applying deep reinforcement learning (DRL) techniques, often enhanced by graph neural networks (GNNs), to solve complex control and optimization problems across diverse domains. Current research emphasizes applications in robotics (trajectory planning, multi-robot coordination, navigation in dynamic environments), wireless communication (UAV control, network optimization), and resource allocation (power arbitrage, task scheduling). These advancements demonstrate the power of DRL, particularly when combined with GNNs for handling relational data, to improve efficiency, robustness, and adaptability in various real-world systems.

Papers

October 30, 2024

From Hype to Reality: The Road Ahead of Deploying DRL in 6G Networks
Haiyuan Li, Hari Madhukumar, Peizheng Li, Yiran Teng, Shuangyi Yan, Dimitra Simeonidou
Deep Reinforcement Learning Real World G Network Built Road Network Slicing Massive Connectivity DRL Algorithm Ga DRL HyPe GT

August 23, 2024

cc-DRL: a Convex Combined Deep Reinforcement Learning Flight Control Design for a Morphing Quadrotor
Tao Yang, Huai-Ning Wu, Jun-Wei Wang
Optimal Control Flight Control Deep Reinforcement Learning Based Free Flight Ga DRL

June 16, 2024

Multi-UAV Multi-RIS QoS-Aware Aerial Communication Systems using DRL and PSO
Marwan Dhuheir, Aiman Erbad, Ala Al-Fuqaha, Mohsen Guizani
Unmanned Aerial Vehicle Particle Swarm Optimization UAV Swarm Optimal Path Planning Ga DRL Multi Robot Aerial System PSO Algorithm

March 25, 2024

Trajectory Planning of Robotic Manipulator in Dynamic Environment Exploiting DRL
Osama Ahmad, Zawar Hussain, Hammad Naeem
Robot Person Dynamic Environment Reinforcement Learning Algorithm Trajectory Planning Robotic Manipulator Deep Deterministic Policy Gradient Degree of Freedom Robot Ga DRL

March 15, 2024

HeR-DRL:Heterogeneous Relational Deep Reinforcement Learning for Decentralized Multi-Robot Crowd Navigation
Xinyu Zhou, Songhao Piao, Wenzheng Chi, Liguo Chen, Wei Li
Reinforcement Learning Crowd Navigation Decentralized Multi Robot Ga DRL

July 30, 2023

DRL4Route: A Deep Reinforcement Learning Framework for Pick-up and Delivery Route Prediction
Xiaowei Mao, Haomin Wen, Hengrui Zhang, Huaiyu Wan, Lixia Wu, Jianbin Zheng, Haoyuan Hu, Youfang Lin
Reinforcement Learning Ga DRL Multi Commodity Pickup Route Prediction

July 24, 2023

Multi-UAV Speed Control with Collision Avoidance and Handover-aware Cell Association: DRL with Action Branching
Zijiang Yan, Wael Jaafar, Bassant Selim, Hina Tabassum
Collision Avoidance Various Fast Moving Drone Action Feature Robot Handover UAV Network Double Deep Q Network Ga DRL Reinforcement Learning Solution Latent Space Communication

July 3, 2023

GA-DRL: Graph Neural Network-Augmented Deep Reinforcement Learning for DAG Task Scheduling over Dynamic Vehicular Clouds
Zhang Liu, Lianfen Huang, Zhibin Gao, Manman Luo, Seyyedali Hosseinalipour, Huaiyu Dai
Deep Reinforcement Learning Graph Neural DAG Learning Ga DRL Subtask Assignment Vehicle Road Cloud

January 19, 2023

Domain-adapted Learning and Imitation: DRL for Power Arbitrage
Yuanrong Wang, Vignesh Raja Swaminathan, Nikita P. Granger, Carlos Ros Perez, Christian Michler
Feature Imitation Domain Adaptive Electricity Market Ga DRL Statistical Arbitrage Energy Arbitrage

January 16, 2023

DRL-VO: Learning to Navigate Through Crowded Dynamic Scenes Using Velocity Obstacles
Zhanteng Xie, Philip Dames
Reinforcement Learning Collision Avoidance Learning Based Robot Learning Based Policy Crowded Scene Ga DRL Velocity Obstacle

September 18, 2022

Evolutionary Deep Reinforcement Learning Using Elite Buffer: A Novel Approach Towards DRL Combined with EA in Continuous Control Tasks
Marzieh Sadat Esmaeeli, Hamed Malek
Reinforcement Learning Deep Reinforcement Learning Evolutionary Algorithm Evolutionary Computation Continuous Control Task Bentonite Buffer Ga DRL

September 1, 2022

DRL Enabled Coverage and Capacity Optimization in STAR-RIS Assisted Networks
Xinyu Gao, Wenqiang Yi, Yuanwei Liu, Jianhua Zhang, Ping Zhang
Wireless Network Higher Coverage Rate PPO Algorithm Ga DRL STAR Ri Capacity Optimization

Ga DRL

Papers

From Hype to Reality: The Road Ahead of Deploying DRL in 6G Networks

cc-DRL: a Convex Combined Deep Reinforcement Learning Flight Control Design for a Morphing Quadrotor

Multi-UAV Multi-RIS QoS-Aware Aerial Communication Systems using DRL and PSO

Trajectory Planning of Robotic Manipulator in Dynamic Environment Exploiting DRL

HeR-DRL:Heterogeneous Relational Deep Reinforcement Learning for Decentralized Multi-Robot Crowd Navigation

DRL4Route: A Deep Reinforcement Learning Framework for Pick-up and Delivery Route Prediction

Multi-UAV Speed Control with Collision Avoidance and Handover-aware Cell Association: DRL with Action Branching

GA-DRL: Graph Neural Network-Augmented Deep Reinforcement Learning for DAG Task Scheduling over Dynamic Vehicular Clouds

Domain-adapted Learning and Imitation: DRL for Power Arbitrage

DRL-VO: Learning to Navigate Through Crowded Dynamic Scenes Using Velocity Obstacles

Evolutionary Deep Reinforcement Learning Using Elite Buffer: A Novel Approach Towards DRL Combined with EA in Continuous Control Tasks

DRL Enabled Coverage and Capacity Optimization in STAR-RIS Assisted Networks