27 citations · 71 across the 5 of their papers we have counts for
5 papers
Runtime-Safety-Guided Policy Repair
Weichao Zhou, Ruihan Gao, BaekGyu Kim +2
We study the problem of policy repair for learning-based control policies in safety-critical settings. We consider an architecture where a high-performance learning-based control p…
Opportunistic Intermittent Control with Safety Guarantees for Autonomous Systems
Chao Huang, Shichao Xu, Zhilu Wang +3
Control schemes for autonomous systems are often designed in a way that anticipates the worst case in any situation. At runtime, however, there could exist opportunities to leverag…
ReachNN: Reachability Analysis of Neural-Network Controlled Systems
Chao Huang, Jiameng Fan, Wenchao Li +2
Applying neural networks as controllers in dynamical systems has shown great promises. However, it is critical yet challenging to verify the safety of such control systems with neu…
Safety-Guided Deep Reinforcement Learning via Online Gaussian Process Estimation
Jiameng Fan, Wenchao Li
An important facet of reinforcement learning (RL) has to do with how the agent goes about exploring the environment. Traditional exploration strategies typically focus on efficienc…
TrojDRL: Trojan Attacks on Deep Reinforcement Learning Agents
Panagiota Kiourti, Kacper Wardega, Susmit Jha +1
Recent work has identified that classification models implemented as neural networks are vulnerable to data-poisoning and Trojan attacks at training time. In this work, we show tha…