2 papers
eess.SY2025
Compositional shield synthesis for safe reinforcement learning in partial observability
Steven Carr, Georgios Bakirtzis, Ufuk Topcu
Agents controlled by the output of reinforcement learning (RL) algorithms often transition to unsafe states, particularly in uncertain and partially observable environments. Partia…
cs.AI2025
Pessimistic Iterative Planning with RNNs for Robust POMDPs
Maris F. L. Galesloot, Marnix Suilen, Thiago D. Simão +4
Robust POMDPs extend classical POMDPs to incorporate model uncertainty using so-called uncertainty sets on the transition and observation functions, effectively defining ranges of…