Deep Reinforcement Learning Approach

Deep reinforcement learning (DRL) employs artificial intelligence to enable agents to learn optimal strategies through trial and error within complex environments. Current research focuses on applying DRL algorithms, such as Deep Q-Networks (DQN), Proximal Policy Optimization (PPO), and Actor-Critic methods (including A3C and DDPG), to diverse problems ranging from resource management (energy grids, battery systems) and traffic optimization to financial trading and autonomous systems (robotics, vehicle navigation). The significance of DRL lies in its ability to solve complex decision-making problems beyond the capabilities of traditional methods, leading to improved efficiency, safety, and resource allocation across various sectors.

Papers

June 23, 2023

Energy Optimization for HVAC Systems in Multi-VAV Open Offices: A Deep Reinforcement Learning Approach
Hao Wang, Xiwen Chen, Natan Vital, Edward. Duffy, Abolfazl Razi
Energy Consumption Energy Efficiency Power Consumption Deep Reinforcement Learning Approach Building Energy Heating, Ventilation, and Air Conditioning Open Plan Office

April 19, 2023

April 11, 2023

Active RIS-aided EH-NOMA Networks: A Deep Reinforcement Learning Approach
Zhaoyuan Shi, Huabing Lu, Xianzhong Xie, Helin Yang, Chongwen Huang, Jun Cai, Zhiguo Ding
Generating User Activity Deep Reinforcement Learning Approach Non Orthogonal Multiple Access Reconfigurable Intelligent Surface Downlink Communication

April 5, 2023

Optimal Energy Storage Scheduling for Wind Curtailment Reduction and Energy Arbitrage: A Deep Reinforcement Learning Approach
Jinhao Li, Changlong Wang, Hao Wang
Deep Reinforcement Learning Approach Wind Power Wind Energy Energy Arbitrage

February 21, 2023

Assessment of Reinforcement Learning for Macro Placement
Chung-Kuan Cheng, Andrew B. Kahng, Sayak Kundu, Yucheng Wang, Zhiang Wang
Reinforcement Learning Direct Assessment Deep Reinforcement Learning Approach Google AI Evaluation Funnel

February 13, 2023

Improving robot navigation in crowded environments using intrinsic rewards
Diego Martinez-Baselga, Luis Riazuelo, Luis Montano
Autonomous Navigation Robot Navigation Intrinsic Reward Crowded Environment Deep Reinforcement Learning Approach Crowd Navigation Exploration Algorithm

February 6, 2023

January 23, 2023

A deep reinforcement learning approach to assess the low-altitude airspace capacity for urban air mobility
Asal Mehditabrizi, Mahdi Samadzad, Sina Sabzekar
Path Planning Various Fast Moving Drone Deep Reinforcement Learning Approach Urban Air Mobility Low Altitude Airspace UAV Path Planning

January 22, 2023

Deep Reinforcement Learning for Concentric Tube Robot Path Following
Keshav Iyengar, Sarah Spurgeon, Danail Stoyanov
Deep Reinforcement Learning Deep Reinforcement Learning Approach Jacobian Computation Concentric Tube Robot Kinematic Error

December 27, 2022

Optimal scheduling of island integrated energy systems considering multi-uncertainties and hydrothermal simultaneous transmission: A deep reinforcement learning approach
Yang Li, Fanjin Bu, Yuanzheng Li, Chao Long
Deep Reinforcement Learning Deep Reinforcement Learning Approach Model Free Deep Reinforcement Learning Energy System Optimal Scheduling Concurrent Transmission Scheduling Framework

December 16, 2022

Reinforcement Learning for Agile Active Target Sensing with a UAV
Harsh Goel, Laura Jarin Lipschitz, Saurav Agarwal, Sandeep Manjanna, Vijay Kumar
Reinforcement Learning Deep Reinforcement Learning Approach Informative Path Planning Active Sensing Uncrewed Aerial Vehicle

November 22, 2022

A Deep Reinforcement Learning Approach to Rare Event Estimation
Anthony Corso, Kyu-Young Kim, Shubh Gupta, Grace Gao, Mykel J. Kochenderfer
Adaptive Importance Deep Reinforcement Learning Approach Rare Event Value Based Reinforcement Learning Monte Carlo Sampling Proposal Distribution

October 2, 2022

Throwing Objects into A Moving Basket While Avoiding Obstacles
Hamidreza Kasaei, Mohammadreza Kasaei
Robot Person Imitation Learning Obstacle Avoidance Robotic Arm Deep Reinforcement Learning Approach Multiple Obstacle Basket Sequence

September 27, 2022

Resource Allocation for Mobile Metaverse with the Internet of Vehicles over 6G Wireless Communications: A Deep Reinforcement Learning Approach
Terence Jie Chua, Wenhan Yu, Jun Zhao
Resource Allocation Augmented Reality Vehicle Plan Ubiquitous Semantic Metaverse Deep Reinforcement Learning Approach G Wireless Virtual World Metaverse Service

September 3, 2022

Model-Free Deep Reinforcement Learning in Software-Defined Networks
Luke Borchjes, Clement Nyirenda, Louise Leenen
Deep Q Network Zero Sum Game Deep Reinforcement Learning Approach Model Free Deep Reinforcement Learning Software Defined Double Deep Q Network Episodic Control

August 22, 2022

Exploring Task-oriented Communication in Multi-agent System: A Deep Reinforcement Learning Approach
Guojun He
Multi Agent Multi Agent System Timely Communication Multi Agent Collaboration Deep Reinforcement Learning Approach Task Oriented Communication

August 10, 2022

Fairness Based Energy-Efficient 3D Path Planning of a Portable Access Point: A Deep Reinforcement Learning Approach
Nithin Babu, Igor Donevski, Alvaro Valcarce, Petar Popovski, Jimmy Jessen Nielsen, Constantinos B. Papadias
Procedural Fairness Unmanned Aerial Vehicle Deep Reinforcement Learning Approach Access Point User Oriented Fairness

July 18, 2022

A Deep Reinforcement Learning Approach for Finding Non-Exploitable Strategies in Two-Player Atari Games
Zihan Ding, Dijia Su, Qinghua Liu, Chi Jin
Markov Game Deep Reinforcement Learning Approach Tabular Markov Decision Process ATARI Game Nash Equilibrium Policy Double DQN

Deep Reinforcement Learning Approach

Papers

Energy Optimization for HVAC Systems in Multi-VAV Open Offices: A Deep Reinforcement Learning Approach

Autonomous Agent for Beyond Visual Range Air Combat: A Deep Reinforcement Learning Approach

H-TSP: Hierarchically Solving the Large-Scale Travelling Salesman Problem

Active RIS-aided EH-NOMA Networks: A Deep Reinforcement Learning Approach

Optimal Energy Storage Scheduling for Wind Curtailment Reduction and Energy Arbitrage: A Deep Reinforcement Learning Approach

Assessment of Reinforcement Learning for Macro Placement

Improving robot navigation in crowded environments using intrinsic rewards

Holistic Deep-Reinforcement-Learning-based Training of Autonomous Navigation Systems

Arena-Web -- A Web-based Development and Benchmarking Platform for Autonomous Navigation Approaches

A deep reinforcement learning approach to assess the low-altitude airspace capacity for urban air mobility

Deep Reinforcement Learning for Concentric Tube Robot Path Following

Optimal scheduling of island integrated energy systems considering multi-uncertainties and hydrothermal simultaneous transmission: A deep reinforcement learning approach

Reinforcement Learning for Agile Active Target Sensing with a UAV

A Deep Reinforcement Learning Approach to Rare Event Estimation

Throwing Objects into A Moving Basket While Avoiding Obstacles

Resource Allocation for Mobile Metaverse with the Internet of Vehicles over 6G Wireless Communications: A Deep Reinforcement Learning Approach

Model-Free Deep Reinforcement Learning in Software-Defined Networks

Exploring Task-oriented Communication in Multi-agent System: A Deep Reinforcement Learning Approach

Fairness Based Energy-Efficient 3D Path Planning of a Portable Access Point: A Deep Reinforcement Learning Approach

A Deep Reinforcement Learning Approach for Finding Non-Exploitable Strategies in Two-Player Atari Games