Latest Articles for Deep Reinforcement Learning

A new model enhances dynamic hedging by accounting for market impact and liquidity.

New method uses deep learning to stabilize power systems with renewables.

A new AI method improves scheduling in uncertain task environments.

A new scheduler improves production efficiency in complex manufacturing environments.

This study focuses on improving adaptability in deep reinforcement learning algorithms.

This article discusses how MBDRL optimizes flow control with efficiency and reduced costs.

New arrival systems for flying vehicles improve city travel efficiency and safety.

A framework using agents empowers users to manage IoT security and privacy preferences.

A new approach to improve voltage regulation with advanced machine learning techniques.

A new approach using AI for effective queue control in real environments.

This study shows how machine learning can improve diagnostic pathways for complex diseases.

Using deep learning to improve public transit efficiency and reduce costs.

AI techniques improve firebreak placement to reduce wildfire spread effectively.

Battery energy storage systems adopt new bidding strategies to optimize market participation.

An overview of deep reinforcement learning in bipedal robot movement.

A new approach improves warfarin dosing clarity and patient care.

Introducing SAFE-RL for clearer decision-making in AI systems.

A new approach improves electricity grid management using target topologies and deep learning.

A new method for quick camera exposure adjustments using deep reinforcement learning.

AARIS technology boosts communication through UAVs, overcoming traditional network challenges.

SINDy-RL improves efficiency and interpretability in control systems using sparse dictionary learning.

This paper explores ways to minimize unnecessary driver interventions in automated vehicles.

A new approach to enhance client availability in federated learning.

Aiming for efficient energy management through smart grids and new technologies.

A new scheduler improves communication in Industrial Internet of Things using reinforcement learning.

A new framework improves decision-making for unmanned combat aerial vehicles in dogfights.

Leveraging reinforcement learning to optimize job scheduling using Gittins index techniques.

A new method enhances trust and decision-making for AI-assisted advice.

Research aims to improve pathfinding efficiency using adaptable heuristic functions.

A new method uses deep reinforcement learning to improve automatic differentiation efficiency.

Research showcases improved robotic arm control using deep reinforcement learning.

Research explores drag reduction in cylinder flow with active control methods and machine learning.

A study on predicting electricity grid failures through deep reinforcement learning analysis.

Study enhances lane-changing strategies for self-driving cars in mixed traffic.

How Mixtures of Experts enhance performance in Deep Reinforcement Learning tasks.

A new method improves routing for electric vehicle deliveries.

Exploring how AAM and DRL improve flight safety and efficiency.

Fluid antennas improve communication and model training in federated learning.

DRLQ enhances task assignment for quantum resources, boosting efficiency in cloud computing.

Investigating qubit allocation and modular architectures for improved quantum computing efficiency.