Tag: reinforcement learning

Researchers report a simulation-based explainability framework that pairs a physics-guided reinforcement learning controller with XGBoost and SHAP analysis to trace ...

A hierarchical Monte Carlo Tree Search framework with staged grid refinements improves truss design quality and cuts computational cost while ...

A new editorial collection documents how artificial intelligence is reshaping particle accelerator science, from surrogate models already in practical use ...

A simulation study reports that an AI-managed electric vehicle charging hub combining solar power, battery storage, LSTM demand forecasting and ...

A hybrid fuzzy rule-based and reinforcement learning scheduler improves real-time traffic reliability, delay, and energy use in Industrial IoT TSCH ...

A reinforcement learning framework improved bandwidth slicing in 5G-advanced O-RAN simulations, while tabular Q-learning struggled with large-state beam selection.

Researchers developed TriAlign-ATG, an AI framework that generates physically executable adversarial network traffic which evades deep-learning intrusion detectors while preserving ...

A resting-state fMRI and machine learning study identified six brain regions whose individualized dysconnectivity patterns distinguished subacute back pain patients ...

An open-source optimization framework developed with CERN has automated accelerator tuning at GSI and FAIR, cutting SIS18 injection losses from ...

A new scoping review of 130 studies finds that reinforcement learning for long-horizon robotic manipulation is dominated by hierarchical methods, ...