research
∙
09/15/2023
Wasserstein Distributionally Robust Control Barrier Function using Conditional Value-at-Risk with Differentiable Convex Programming
Control Barrier functions (CBFs) have attracted extensive attention for ...
share
research
∙
05/05/2023
On the Optimality, Stability, and Feasibility of Control Barrier Functions: An Adaptive Learning-Based Approach
Safety has been a critical issue for the deployment of learning-based ap...
research
∙
03/07/2022
Influencing Long-Term Behavior in Multiagent Reinforcement Learning
The main challenge of multiagent reinforcement learning is the difficult...
research
∙
09/14/2021
ROMAX: Certifiably Robust Deep Multiagent Reinforcement Learning via Convex Relaxation
In a multirobot system, a number of cyber-physical attacks (e.g., commun...
research
∙
08/09/2021
Reachability Analysis of Neural Feedback Loops
Neural Networks (NNs) can provide major empirical performance improvemen...
research
∙
10/31/2020
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
A fundamental challenge in multiagent reinforcement learning is to learn...
research
∙
06/19/2020
Set-Invariant Constrained Reinforcement Learning with a Meta-Optimizer
This paper investigates reinforcement learning with safety constraints. ...
research
∙
03/02/2020