5 papers
Wasserstein Barycenter Soft Actor-Critic
Zahra Shahrooei, Ali Baheri
Deep off-policy actor-critic algorithms have emerged as the leading framework for reinforcement learning in continuous control domains. However, most of these algorithms suffer fro…
Optimal Transport-Guided Safety in Temporal Difference Reinforcement Learning
Zahra Shahrooei, Ali Baheri
The primary goal of reinforcement learning is to develop decision-making policies that prioritize optimal performance, frequently without considering safety. In contrast, safe rein…
Optimizing Falsification for Learning-Based Control Systems: A Multi-Fidelity Bayesian Approach
Zahra Shahrooei, Mykel J. Kochenderfer, Ali Baheri
Testing controllers in safety-critical systems is vital for ensuring their safety and preventing failures. In this paper, we address the falsification problem within learning-based…
Optimal Transport-Assisted Risk-Sensitive Q-Learning
Zahra Shahrooei, Ali Baheri
The primary goal of reinforcement learning is to develop decision-making policies that prioritize optimal performance without considering risk or safety. In contrast, safe reinforc…
Falsification of Learning-Based Controllers through Multi-Fidelity Bayesian Optimization
Zahra Shahrooei, Mykel J. Kochenderfer, Ali Baheri
Simulation-based falsification is a practical testing method to increase confidence that the system will meet safety requirements. Because full-fidelity simulations can be computat…