Double Deep Q Network

Double Deep Q-Networks (DDQN) are a reinforcement learning technique used to train agents to make optimal sequential decisions in complex environments. Current research focuses on applying DDQN, often in conjunction with other architectures like recurrent neural networks and attention mechanisms, to diverse problems such as UAV path planning, autonomous vehicle navigation, and cybersecurity in software-defined networks. This approach offers improved performance over simpler Q-learning methods, particularly in scenarios with high dimensionality or adversarial interactions, leading to more efficient and robust solutions in various domains.

Papers

November 6, 2024

Human-in-the-Loop Feature Selection Using Interpretable Kolmogorov-Arnold Network-based Double Deep Q-Network
Md Abrar Jahin, M. F. Mridha, Nilanjan Dey
Inherent Interpretability Kolmogorov Arnold Network Human in the Loop Interpretable Way Double Deep Q Network

November 3, 2024

Two-Timescale Model Caching and Resource Allocation for Edge-Enabled AI-Generated Content Services
Zhang Liu, Hongyang Du, Xiangwang Hou, Lianfen Huang, Seyyedali Hosseinalipour, Dusit Niyato, Khaled Ben Letaief
Deep Reinforcement Learning Generative AI Resource Allocation Generated Content Content Creator Double Deep Q Network Mobile Artificial Intelligence Generated Content

May 17, 2024

ARDDQN: Attention Recurrent Double Deep Q-Network for UAV Coverage Path Planning and Data Harvesting
Praveen Kumar, Priyadarshni, Rajiv Misra
Recurrent Neural Network Unmanned Aerial Vehicle Data Collection Coverage Path Planning Double Deep Q Network

April 26, 2024

Adaptive speed planning for Unmanned Vehicle Based on Deep Reinforcement Learning
Hao Liu, Yi Shen, Wenjing Zhou, Yuelin Zou, Chang Zhou, Shuyao He
Deep Reinforcement Learning Deep Q Network Efficient Path Planning Unmanned Vehicle Double Deep Q Network Speed Planning

October 15, 2023

Deep Reinforcement Learning with Explicit Context Representation
Francisco Munguia-Galeano, Ah-Hwee Tan, Ze Ji
Reinforcement Learning Deep Reinforcement Learning Deep Q Network Contextual Representation Double Deep Q Network

August 9, 2023

Adversarial Deep Reinforcement Learning for Cyber Security in Software Defined Networks
Luke Borchjes, Clement Nyirenda, Louise Leenen
Deep Reinforcement Learning Deep Q Network Software Defined Adversarial Reinforcement Learning Cyber Security Double Deep Q Network

July 27, 2023

Reinforcement learning guided fuzz testing for a browser's HTML rendering engine
Martin Sablotny, Bjørn Sand Jensen, Jeremy Singer
Reinforcement Learning Fuzz Testing Efficient Engine Double Deep Q Network HTML Document Web Browser

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

February 15, 2023

Deep Offline Reinforcement Learning for Real-world Treatment Optimization Applications
Milashini Nambiar, Supriyo Ghosh, Priscilla Ong, Yu En Chan, Yong Mong Bee, Pavitra Krishnaswamy
Reinforcement Learning Policy Reinforcement Learning Conservative Q Learning Double Deep Q Network Optimal Treatment

January 26, 2023

Double Deep Reinforcement Learning Techniques for Low Dimensional Sensing Mapless Navigation of Terrestrial Mobile Robots
Linda Dotto de Moraes, Victor Augusto Kich, Alisson Henrique Kolling, Jair Augusto Bottega, Raul Steinmetz, Emerson Cassiano da Silva, Ricardo Bedin Grando, Anselmo Rafael Cuckla, Daniel Fernando Tello Gamarra
Deep Reinforcement Learning Deep Q Network Deep RL Double Deep Q Network Terrestrial Mobile Robot

November 24, 2022

Double Deep Q-Learning in Opponent Modeling
Yangtianze Tao, John Doe
Multi Agent System Opponent Modeling Diving Deep Double Deep Q Network Mixture of Expert Architecture

October 14, 2022

ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning
Tiantian Chen, Siwen Yan, Jianxiong Guo, Weili Wu
Deep Reinforcement Learning Influence Maximization Large Scale Network Double Deep Q Network Effective Solution

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

June 28, 2022

Applications of Reinforcement Learning in Finance -- Trading with a Double Deep Q-Network
Frensi Zejnullahu, Maurice Moser, Joerg Osterrieder
Reinforcement Learning Financial Application Financial Trading Continuous Option Double Deep Q Network

May 28, 2022

Survival Analysis on Structured Data using Deep Reinforcement Learning
Renith G, Harikrishna Warrier, Yogesh Gupta
Deep Learning Deep Reinforcement Learning Structured Data Predictive Maintenance Double Deep Q Network

May 27, 2022

Double Deep Q Networks for Sensor Management in Space Situational Awareness
Benedict Oakes, Dominic Richards, Jordi Barr, Jason F. Ralph
Reinforcement Learning Situational Awareness Space Domain Awareness Double Deep Q Network Sensor Management

Double Deep Q Network

Papers

Human-in-the-Loop Feature Selection Using Interpretable Kolmogorov-Arnold Network-based Double Deep Q-Network

Two-Timescale Model Caching and Resource Allocation for Edge-Enabled AI-Generated Content Services

ARDDQN: Attention Recurrent Double Deep Q-Network for UAV Coverage Path Planning and Data Harvesting

Adaptive speed planning for Unmanned Vehicle Based on Deep Reinforcement Learning

Deep Reinforcement Learning with Explicit Context Representation

Adversarial Deep Reinforcement Learning for Cyber Security in Software Defined Networks

Reinforcement learning guided fuzz testing for a browser's HTML rendering engine

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

Deep Offline Reinforcement Learning for Real-world Treatment Optimization Applications

Double Deep Reinforcement Learning Techniques for Low Dimensional Sensing Mapless Navigation of Terrestrial Mobile Robots

Double Deep Q-Learning in Opponent Modeling

ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning

Model-Free Deep Reinforcement Learning in Software-Defined Networks

Applications of Reinforcement Learning in Finance -- Trading with a Double Deep Q-Network

Survival Analysis on Structured Data using Deep Reinforcement Learning

Double Deep Q Networks for Sensor Management in Space Situational Awareness