2 citations · 6 across the 13 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…
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…
Certified Policy Verification and Synthesis for MDPs under Distributional Reach-avoidance Properties
S. Akshay, Krishnendu Chatterjee, Tobias Meggendorfer +1
Markov Decision Processes (MDPs) are a classical model for decision making in the presence of uncertainty. Often they are viewed as state transformers with planning objectives defi…
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…