3 citations · 3 across the 8 of their papers we have counts for
3 papers · 1 filter
Realizable Continuous-Space Shields for Safe Reinforcement Learning
Kyungmin Kim, Davide Corsi, Andoni Rodriguez +5
While Deep Reinforcement Learning (DRL) has achieved remarkable success across various domains, it remains vulnerable to occasional catastrophic failures without additional safegua…
Make the Pertinent Salient: Task-Relevant Reconstruction for Visual Control with Distractions
Kyungmin Kim, JB Lanier, Pierre Baldi +2
Recent advancements in Model-Based Reinforcement Learning (MBRL) have made it a powerful tool for visual control tasks. Despite improved data efficiency, it remains challenging to…
Reinforcement Learning from Delayed Observations via World Models
Armin Karamzade, Kyungmin Kim, Montek Kalsi +1
In standard reinforcement learning settings, agents typically assume immediate feedback about the effects of their actions after taking them. However, in practice, this assumption…