19 citations · 25 across the 8 of their papers we have counts for
11 papers
Lyapunov Robust Constrained-MDPs: Soft-Constrained Robustly Stable Policy Optimization under Model Uncertainty
Reazul Hasan Russel, Mouhacine Benosman, Jeroen Van Baar +1
Safety and robustness are two desired properties for any reinforcement learning algorithm. CMDPs can handle additional safety constraints and RMDPs can perform well under model unc…
Robust Constrained-MDPs: Soft-Constrained Robust Policy Optimization under Model Uncertainty
Reazul Hasan Russel, Mouhacine Benosman, Jeroen Van Baar
In this paper, we focus on the problem of robustifying reinforcement learning (RL) algorithms with respect to model uncertainties. Indeed, in the framework of model-based RL, we pr…
Entropic Risk Constrained Soft-Robust Policy Optimization
Reazul Hasan Russel, Bahram Behzadian, Marek Petrik
Having a perfect model to compute the optimal policy is often infeasible in reinforcement learning. It is important in high-stakes domains to quantify and manage risk induced by mo…
Optimizing Norm-Bounded Weighted Ambiguity Sets for Robust MDPs
Reazul Hasan Russel, Bahram Behzadian, Marek Petrik
Optimal policies in Markov decision processes (MDPs) are very sensitive to model misspecification. This raises serious concerns about deploying them in high-stake domains. Robust M…
A Probabilistic Approach to Satisfiability of Propositional Logic Formulae
Reazul Hasan Russel
We propose a version of WalkSAT algorithm, named as BetaWalkSAT. This method uses probabilistic reasoning for biasing the starting state of the local search algorithm. Beta distrib…
Optimizing Percentile Criterion Using Robust MDPs
Bahram Behzadian, Reazul Hasan Russel, Marek Petrik +1
We address the problem of computing reliable policies in reinforcement learning problems with limited data. In particular, we compute policies that achieve good returns with high c…