Latest Articles for Deep Reinforcement Learning

XP-HARQ improves data transmission efficiency for fast-response applications.

Learn how to optimize digital twin migration for enhanced user experiences in vehicular metaverses.

Exploring innovative approaches to enhance robotic pathfinding in complex environments.

Explore the impact of generative diffusion models in various fields, especially network optimization.

New approach automates reward function design for deep reinforcement learning in robots.

This article discusses DRL techniques for improved scheduling in IoT environments.

New method allows quadrupedal robots to learn dynamic movements more effectively.

Improving task scheduling strategies for mobile applications using deep reinforcement learning.

Research reveals new insights into deep reinforcement learning through game challenges.

A new system enhances AV decision-making during road construction.

Exploring how robot design influences movement and task learning.

Exploring the impact of deep learning on engineering simulations and modeling.

A look at integrating Deep Reinforcement Learning in UAV systems for better performance and safety.

A novel approach merges two methods for better problem-solving.

TbDd framework improves blockchain security and efficiency for IoT applications.

New technology optimizes internet connectivity using Integrated Access and Backhaul networks.

Deep learning techniques improve monitoring and optimization in electric power systems.

This study highlights the sample complexity of Neural Policy Mirror Descent algorithms in deep learning.

ASVs improve efficiency in tracking water quality for safer environments.

A new method improves evolutionary algorithms for complex optimization problems.

A new method improves test generation based on natural language requirements.

A new framework enhances GPU performance for deep learning tasks.

This work proposes a robust approach for deep reinforcement learning against input data attacks.

Using deep reinforcement learning for better data traffic management.

Robots improve data collection efficiency with dynamic path planning in unknown environments.

Adaptive AI techniques improve access management in diverse Metaverse environments.

This study compares evolution strategies and deep reinforcement learning in various tasks.

CEQR-DQN enhances decision-making by effectively managing uncertainties in AI.

A DRL agent wins IEEE microRTS competition, showcasing AI potential in gaming.

A new algorithm improves task offloading efficiency in mobile edge computing environments.

Exploring DRL's effectiveness in managing temperature with cooling jets on hot surfaces.

This article discusses improving mobile edge computing through joint optimization techniques.

A method using deep reinforcement learning and reactive synthesis for controller design.

Research explores advanced methods to understand fish swimming and improve design of aquatic robots.

A study on using deep reinforcement learning for better flow control in structures.

A novel approach for improving cellular reprogramming strategies using deep reinforcement learning.

This study improves maintenance scheduling using deep reinforcement learning for industrial machines.

A new method enhances robots' abilities to move efficiently on uneven surfaces.

A new model aims to reward NFT creators over time.

This article analyzes DRL algorithms for energy-efficient HVAC systems in buildings.