2 citations · 2 across the 8 of their papers we have counts for
8 papers
Verifiable Foundation Models for Robot Safety
Davide Corsi, Kyungmin Kim, Roy Fox
Deploying foundation models for robot control raises a central challenge: the expressive power that enables rich, multimodal perception also makes these models opaque and difficult…
Model-Based Reinforcement Learning under Random Observation Delays
Armin Karamzade, Kyungmin Kim, JB Lanier +2
Delays frequently occur in real-world environments, yet standard reinforcement learning (RL) algorithms often assume instantaneous perception of the environment. We study random se…
Explanations for Unrealizability of Infinite-State Safety Shields
Andoni Rodriguez, Irfansha Shaik, Davide Corsi +2
Safe Reinforcement Learning focuses on developing optimal policies while ensuring safety. A popular method to address such task is shielding, in which a correct-by-construction saf…
Efficient Dynamic Shielding for Parametric Safety Specifications
Davide Corsi, Kaushik Mallik, Andoni Rodriguez +1
Shielding has emerged as a promising approach for ensuring safety of AI-controlled autonomous systems. The algorithmic goal is to compute a shield, which is a runtime safety enforc…
Adapting World Models with Latent-State Dynamics Residuals
JB Lanier, Kyungmin Kim, Armin Karamzade +5
Simulation-to-reality reinforcement learning (RL) faces the critical challenge of reconciling discrepancies between simulated and real-world dynamics, which can severely degrade ag…
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…
Verification-Guided Shielding for Deep Reinforcement Learning
Davide Corsi, Guy Amir, Andoni Rodriguez +3
In recent years, Deep Reinforcement Learning (DRL) has emerged as an effective approach to solving real-world tasks. However, despite their successes, DRL-based policies suffer fro…
Shield Synthesis for LTL Modulo Theories
Andoni Rodriguez, Guy Amir, Davide Corsi +2
In recent years, Machine Learning (ML) models have achieved remarkable success in various domains. However, these models also tend to demonstrate unsafe behaviors, precluding their…