1 citations · 1 across the 5 of their papers we have counts for
6 papers
Provably Safe Reinforcement Learning for Stochastic Reach-Avoid Problems with Entropy Regularization
Abhijit Mazumdar, Rafal Wisniewski, Manuela L. Bujorianu
We consider the problem of learning the optimal policy for Markov decision processes with safety constraints. We formulate the problem in a reach-avoid setup. Our goal is to design…
An Online Multiobjective Policy Gradient for Long-run Average-reward Markov Decision Process
Rahul Misra, Manuela L. Bujorianu, Rafał Wisniewski
We propose a reinforcement learning (RL) framework for multi-objective decision-making, where the agent seeks to optimize a vector of rewards rather than a single scalar value. The…
Distributionally Robust Safety Verification for Markov Decision Processes
Abhijit Mazumdar, Yuting Hou, Rafal Wisniewski
In this paper, we propose a distributionally robust safety verification method for Markov decision processes where only an ambiguous transition kernel is available instead of the p…
Large Deviations in Safety-Critical Systems with Probabilistic Initial Conditions
Aitor R. Gomez, Manuela L. Bujorianu, Rafal Wisniewski
We often rely on probabilistic measures -- e.g. event probability or expected time -- to characterize systems' safety. However, determining these quantities for extremely low-proba…
Safe Reinforcement Learning for Constrained Markov Decision Processes with Stochastic Stopping Time
Abhijit Mazumdar, Rafal Wisniewski, Manuela L. Bujorianu
In this paper, we present an online reinforcement learning algorithm for constrained Markov decision processes with a safety constraint. Despite the necessary attention of the scie…
Online Model-free Safety Verification for Markov Decision Processes Without Safety Violation
Abhijit Mazumdar, Rafal Wisniewski, Manuela L. Bujorianu
In this paper, we consider the problem of safety assessment for Markov decision processes without explicit knowledge of the model. We aim to learn probabilistic safety specificatio…