30 citations · 36 across the 12 of their papers we have counts for
4 papers · 1 filter
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…
Reinforcement Learning of Risk-Constrained Policies in Markov Decision Processes
Tomas Brazdil, Krishnendu Chatterjee, Petr Novotny +1
Markov decision processes (MDPs) are the defacto frame-work for sequential decision making in the presence ofstochastic uncertainty. A classical optimization criterion forMDPs is t…
Expectation Optimization with Probabilistic Guarantees in POMDPs with Discounted-sum Objectives
Krishnendu Chatterjee, Adrián Elgyütt, Petr Novotný +1
Partially-observable Markov decision processes (POMDPs) with discounted-sum payoff are a standard framework to model a wide range of problems related to decision making under uncer…
Optimizing Expectation with Guarantees in POMDPs (Technical Report)
Krishnendu Chatterjee, Petr Novotný, Guillermo A. Pérez +2
A standard objective in partially-observable Markov decision processes (POMDPs) is to find a policy that maximizes the expected discounted-sum payoff. However, such policies may st…