The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...
How do electrical signals become "about" something? Through purely physical processes, neural networks transform activity ...
The challenge, then, is not external hostility or social exclusion. It is continuity under minority conditions. When a tradition is visible without being formative, celebrated without being taught, ...
Abstract: We propose MoRe-ERL, a framework that combines Episodic Reinforcement Learning (ERL) and residual learning, which refines preplanned reference trajectories into safe, feasible, and efficient ...
Abstract: A differential dynamic programming (DDP)-based framework for inverse reinforcement learning (IRL) is introduced to recover the parameters in the cost function, system dynamics, and ...
Higher education institutions (HEIs) worldwide face mounting pressures to transform their organizational cultures in response to the Fourth Industrial Revolution (4IR), socio-political imperatives, ...
The new reinforcement learning system lets large language models challenge and improve themselves using real-world data instead of curated training sets. Meta researchers have unveiled a new ...
Introduction: Cardiovascular-retinal pathophysiology represents an emerging frontier in precision medicine, with hypertensive retinopathy (HR) serving as a critical biomarker for systemic vascular ...
Background: End-diastolic (ED) and end-systolic (ES) frames are critical for left ventricular (LV) volume measurements in echocardiography but show high inter- and intra-observer variability. Deep ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results