Results 81 to 90 of about 6,813,126 (333)
Q-Match: Self-Supervised Learning by Matching Distributions Induced by a Queue [PDF]
, 2023 Thomas Mulc, Debidatta Dwibedi
openalex +1 more source
EMBEDDED LEARNING ROBOT WITH FUZZY Q-LEARNING FOR OBSTACLE AVOIDANCE BEHAVIOR [PDF]
, 2009 Fuzzy Q-learning is extending of Q-learning algorithm that uses fuzzy inference system to enable Q-learning holding continuous action and state. This learning has been implemented in various robot learning application like obstacle avoidance and target ...
Anam, Khairul
core
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu +10 more
wiley +1 more source
Cyberattack Correlation and Mitigation for Distribution Systems via Machine Learning
IEEE Open Access Journal of Power and Energy, 2023 Cyber-physical system security for electric distribution systems is critical. In direct switching attacks, often coordinated, attackers seek to toggle remote-controlled switches in the distribution network.
Jennifer Appiah-Kubi, Chen-Ching Liu
doaj +1 more source
Multi-Agent Advisor Q-Learning (Extended Abstract) [PDF]
, 2023 Sriram Ganapathi Subramanian +3 more
openalex +1 more source
, 2018 Distributional reinforcement learning (distributional RL) has seen empirical success in complex Markov Decision Processes (MDPs) in the setting of nonlinear function approximation. However, there are many different ways in which one can leverage the distributional approach to reinforcement learning.
Doan, Thang +2 more
openaire +2 more sources
Arthritis Care &Research, Accepted Article.Objective This study aimed to characterize the pharmacokinetics, pharmacodynamics, safety, and exploratory efficacy of subcutaneous belimumab in pediatric patients with active systemic lupus erythematosus (SLE) receiving standard therapy. Methods This single‐arm, multicenter, open‐label trial (GSK study 200908; NCT04179032) used three‐weight‐band ...
Hermine I. Brunner +14 more
wiley +1 more source
Composable Deep Reinforcement Learning for Robotic Manipulation
, 2018 Model-free deep reinforcement learning has been shown to exhibit good performance in domains ranging from video games to simulated robotic manipulation and locomotion. However, model-free methods are known to perform poorly when the interaction time with
Abbeel, Pieter +5 more
core +1 more source
Cognitive Behavioral Therapy for Youth with Childhood‐Onset Lupus: A Randomized Clinical Trial
Arthritis Care &Research, Accepted Article.Objective Our objective was to determine the feasibility and acceptability of the Treatment and Education Approach for Childhood‐onset Lupus (TEACH), a six‐session cognitive behavioral intervention addressing depressive, fatigue, and pain symptoms, delivered remotely to individual youth with lupus by a trained interventionist.
Natoshia R. Cunningham +29 more
wiley +1 more source
Addressing Function Approximation Error in Actor-Critic Methods [PDF]
, 2018 In value-based reinforcement learning methods such as deep Q-learning, function approximation errors are known to lead to overestimated value estimates and suboptimal policies.
Fujimoto, Scott +2 more
core +1 more source