3 papers
cs.LG2026
Nightmare Dreamer: Dreaming About Unsafe States And Planning Ahead
Oluwatosin Oseni, Shengjie Wang, Jun Zhu +1
Reinforcement Learning (RL) has shown remarkable success in real-world applications, particularly in robotics control. However, RL adoption remains limited due to insufficient safe…
cs.LG2025
When a Reinforcement Learning Agent Encounters Unknown Unknowns
Juntian Zhu, Miguel de Carvalho, Zhouwang Yang +1
An AI agent might surprisingly find she has reached an unknown state which she has never been aware of -- an unknown unknown. We mathematically ground this scenario in reinforcemen…
math.OC2025
A Regularized Newton Method for Nonconvex Optimization with Global and Local Complexity Guarantees
Yuhao Zhou, Jintao Xu, Bingrui Li +3
Finding an -stationary point of a nonconvex function with a Lipschitz continuous Hessian is a central problem in optimization. Regularized Newton methods are a classical tool an…