Optimal Tracking Control of a Nonlinear Multiagent System Using Q-Learning via Event-Triggered Reinforcement Learning. [PDF]
Entropy (Basel), 2023 Wang Z, Wang X, Tang Y, Liu Y, Hu J.
europepmc +1 more source
Advanced Science, EarlyView.This study shows that gene replacement therapy using the AAV2/Anc80L65 virus can successfully restore hearing and balance in Ush1c knockout mice. The treatment leads to lasting improvements in both auditory and vestibular functions, highlighting its potential as a therapeutic approach for genetic hearing loss and vestibular disorders in humans ...
Weinan Du +13 more
wiley +1 more source
Enhancing the Efficiency of a Cybersecurity Operations Center Using Biomimetic Algorithms Empowered by Deep Q-Learning. [PDF]
Biomimetics (Basel)Olivares R +4 more
europepmc +1 more source
Minibatch Recursive Least Squares Q-Learning. [PDF]
Comput Intell Neurosci, 2021 Zhang C, Song Q, Meng Z.
europepmc +1 more source
Hierarchical Nash-Cournot Q-Learning in Electricity Markets
, 2008 M. Sahraee Ardakani +2 more
openalex +1 more source
Fuzzy Q learning algorithm for dual-aircraft path planning to cooperatively detect targets by passive radars [PDF]
, 2013 Gao Xiang, Yangwang Fang, Youli Wu
openalex +1 more source
Large‐Scale Plasma Proteomics to Profile Pathways and Prognosis of Chronic Pain
Advanced Science, EarlyView.This study delineates both common and site‐specific proteins linked to various chronic pain conditions, elucidating their implications across molecular pathways and health status. These findings, particularly those proteins with genetic causal links to pain or predictive capabilities, have the potential to significantly benefit both research and ...
Ze‐Yu Li +17 more
wiley +1 more source
A Temporal Deep Q Learning for Optimal Load Balancing in Software-Defined Networks. [PDF]
Sensors (Basel)Sharma A +2 more
europepmc +1 more source
Advanced Science, EarlyView.This study uses gut microbiome data to predict corticosteroid response in patients with immune thrombocytopenia (ITP). Fecal samples from 212 patients with ITP are sequenced. Six machine‐learning algorithms are used to train predictive models. The support vector machine‐based model integrated clinical data and selected microbial species, diversities ...
Feng‐Qi Liu +38 more
wiley +1 more source
Optimizing Human-Robot Teaming Performance through Q-Learning-Based Task Load Adjustment and Physiological Data Analysis. [PDF]
Sensors (Basel)Korivand S +4 more
europepmc +1 more source