Results 61 to 70 of about 301,921 (265)

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

Multiagent Deep Reinforcement Learning Algorithms in StarCraft II: A Review

IEEE Access
StarCraft II, as a real-time strategy game, features multiagent collaboration, complex decision-making processes, partially observable environments, and long-term credit assignment; thus, it is an ideal platform for exploring, validating, and optimizing ...
Yanyan Li, Yijun Wang, Yiwei Zhou
doaj   +1 more source

LFDC: Low-Energy Federated Deep Reinforcement Learning for Caching Mechanism in Cloud–Edge Collaborative

Applied Sciences, 2023
The optimization of caching mechanisms has long been a crucial research focus in cloud–edge collaborative environments. Effective caching strategies can substantially enhance user experience quality in these settings.
Xinyu Zhang, Zhigang Hu, Meiguang Zheng, Yang Liang, Hui Xiao, Hao Zheng, Aikun Xu   +6 more
doaj   +1 more source

Clinical, histological, and serological predictors of renal function loss in lupus nephritis.

Arthritis Care &Research, Accepted Article.
Objective Kidney survival is the ultimate goal in lupus nephritis (LN) management, but long‐term predictors remain inadequately studied, requiring long‐term follow‐up. This study aimed to identify baseline and early longitudinal predictors of kidney survival in the Accelerating Medicines Partnership LN longitudinal cohort.
Shangzhu Zhang, Laurence Magder, Daniel Goldman, Judith A. James, Joel M Guthridge, Carla Guthridge, Peter Izmirly, Jill P Buyon, H.Michael Belmont, Richard A. Furie, Noa Schwartz, Chaim Putterman, Jennifer L. Barnas, Jennifer H. Anolik, Sarah French, Maria Dall'era, Avi Z. Rosenberg, Jeffrey Hodgin, Dawit S. Demeke, the Accelerating Medicines Partnership RA/SLE Network, Michelle Petri, Andrea Fava   +21 more
wiley   +1 more source

Deep Reinforcement Learning

2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2023
Branka Hadji Misheva, Joerg Osterrieder
  +5 more sources

A new approach for drone tracking with drone using Proximal Policy Optimization based distributed deep reinforcement learning

SoftwareX, 2023
In this paper, a distributed deep reinforcement learning algorithm based on Proximal Policy Optimization (PPO) is proposed for an unmanned aerial vehicle (UAV) to autonomously track another UAV. Accordingly, this paper makes three important contributions
Ziya Tan, Mehmet Karaköse
doaj   +1 more source

Deep Reinforcement Learning for Dialogue Generation

, 2016
Recent neural models of dialogue generation offer great promise for generating responses for conversational agents, but tend to be shortsighted, predicting utterances one at a time while ignoring their influence on future outcomes.
Galley, Michel, Gao, Jianfeng, Jurafsky, Dan, Li, Jiwei, Monroe, Will, Ritter, Alan   +5 more
core   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

A Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller

International Journal of Adaptive Control and Signal Processing, EarlyView.
Block Diagram of the Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller. ABSTRACT This article introduces a discrete‐time robust adaptive one‐sample‐ahead preview super‐twisting sliding mode controller. A stability analysis of the controller by Lyapunov criteria is developed to demonstrate its robustness in handling both ...
Guilherme Vieira Hollweg, Paulo Jefferson Dias de Oliveira Evald, Shivam Chaturvedi, Hilton Abilio Gründling, Rodrigo Varella Tambara, Wencong Su   +5 more
wiley   +1 more source

Quality of service optimization algorithm based on deep reinforcement learning in software defined network

物联网学报, 2023
Deep reinforcement learning has strong abilities of decision-making and generalization and often applies to the quality of service (QoS) optimization in software defined network (SDN).However, traditional deep reinforcement learning algorithms have ...
Cenhuishan LIAO, Junyan CHEN, Guanping LIANG, Xiaolan XIE, Xiaoye LU   +4 more
doaj   +2 more sources