3 papers
cs.LG2026
Safe Continual Reinforcement Learning under Nonstationarity via Adaptive Safety Constraints
Timofey Tomashevskiy
Safe reinforcement learning in nonstationary environments requires safety mechanisms that adapt as environmental conditions change. Standard safe reinforcement learning methods oft…
cs.LG2026
From Cumulative Constraints to Adaptive Runtime Safety Control for Nonstationary Reinforcement Learning
Timofey Tomashevskiy
Safety in reinforcement learning is often specified through cumulative cost constraints, but these trajectory-level guarantees do not directly prevent unsafe individual decisions,…
cs.LG2026
Safe Continual Reinforcement Learning Methods for Nonstationary Environments. Towards a Survey of the State of the Art
Timofey Tomashevskiy
This work provides a state-of-the-art survey of continual safe online reinforcement learning (COSRL) methods. We discuss theoretical aspects, challenges, and open questions in buil…