2 citations · 3 across the 12 of their papers we have counts for
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Quantitative Analysis of -Regular Robust MDPs
Ali Asadi, Krishnendu Chatterjee, Ehsan Kafshdar Goharshady +3
Robust Markov Decision Processes (RMDPs) generalize classical MDPs by allowing uncertainty in transition probabilities and optimizing against their worst-case realization. We consi…
Automated Approach for Solving Infinite-state Polynomial Reachability Games
Krishnendu Chatterjee, Ehsan Kafshdar Goharshady, Mehrdad Karrabi +2
Reachability games are two-player games played on a graph, where the objective of player is to reach the target set whereas the objective of player…
Strongly Polynomial Time Complexity of Policy Iteration for Robust MDPs
Ali Asadi, Krishnendu Chatterjee, Ehsan Goharshady +3
Markov decision processes (MDPs) are a fundamental model in sequential decision making. Robust MDPs (RMDPs) extend this framework by allowing uncertainty in transition probabilitie…
Qualitative Analysis of -Regular Objectives on Robust MDPs
Ali Asadi, Krishnendu Chatterjee, Ehsan Kafshdar Goharshady +2
Robust Markov Decision Processes (RMDPs) generalize classical MDPs that consider uncertainties in transition probabilities by defining a set of possible transition functions. An ob…
Solving Long-run Average Reward Robust MDPs via Stochastic Games
Krishnendu Chatterjee, Ehsan Kafshdar Goharshady, Mehrdad Karrabi +2
Markov decision processes (MDPs) provide a standard framework for sequential decision making under uncertainty. However, MDPs do not take uncertainty in transition probabilities in…