6 papers
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…
On the Complexity of Discounted Robust MDPs with Uncertainty Sets
Ali Asadi, Krishnendu Chatterjee, Alipasha Montaseri +1
A basic model in sequential decision making is the Markov decision process (MDP), which is extended to Robust MDPs (RMDPs) by allowing uncertainty in transition probabilities and o…
Randomise Alone, Reach as a Team
Léonard Brice, Thomas A. Henzinger, Alipasha Montaseri +2
We study concurrent graph games where n players cooperate against an opponent to reach a set of target states. Unlike traditional settings, we study distributed randomisation: team…
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…
How Bad Is Forming Your Own Multidimensional Opinion?
Kiarash Banihashem, MohammadTaghi Hajiaghayi, Mahdi JafariRaviz +2
Understanding the formation of opinions on interconnected topics within social networks is of significant importance. It offers insights into collective behavior and decision-makin…
Model-Agnostic Approximation of Constrained Forest Problems
Corinna Coupette, Alipasha Montaseri, Christoph Lenzen
Constrained Forest Problems (CFPs) as introduced by Goemans and Williamson in 1995 capture a wide range of network design problems with edge subsets as solutions, such as Minimum S…