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08/05/2021
Lyapunov Robust Constrained-MDPs: Soft-Constrained Robustly Stable Policy Optimization under Model Uncertainty
Safety and robustness are two desired properties for any reinforcement l...
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10/10/2020
Robust Constrained-MDPs: Soft-Constrained Robust Policy Optimization under Model Uncertainty
In this paper, we focus on the problem of robustifying reinforcement lea...
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06/20/2020
Entropic Risk Constrained Soft-Robust Policy Optimization
Having a perfect model to compute the optimal policy is often infeasible...
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12/04/2019
A Probabilistic Approach to Satisfiability of Propositional Logic Formulae
We propose a version of WalkSAT algorithm, named as BetaWalkSAT. This me...
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12/04/2019
Optimizing Norm-Bounded Weighted Ambiguity Sets for Robust MDPs
Optimal policies in Markov decision processes (MDPs) are very sensitive ...
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10/23/2019
High-Confidence Policy Optimization: Reshaping Ambiguity Sets in Robust MDPs
Robust MDPs are a promising framework for computing robust policies in r...
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01/21/2019
A Short Survey on Probabilistic Reinforcement Learning
A reinforcement learning agent tries to maximize its cumulative payoff b...
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11/15/2018
Tight Bayesian Ambiguity Sets for Robust MDPs
Robustness is important for sequential decision making in a stochastic d...
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04/12/2017