3 papers
eess.SY2026
Kernel-Based Safe Exploration in Deep Reinforcement Learning
Rupak Majumdar, Nikhil Singh, Sadegh Soudjani
Safety has been a major concern when deploying deep reinforcement learning algorithms in the real world. A promising direction that ensures that the learned policy does not visit u…
cs.GT2026
Solving Qualitative Multi-Objective Stochastic Games
Moritz Graf, Anthony Lin, Rupak Majumdar
Many problems in compositional synthesis and verification of multi-agent systems -- such as rational verification and assume-guarantee verification in probabilistic systems -- redu…
cs.GT2025
Value-Set Iteration: Computing Optimal Correlated Equilibria in Infinite-Horizon Multi-Player Stochastic Games
Jiarui Gan, Rupak Majumdar
We study the problem of computing optimal correlated equilibria (CEs) in infinite-horizon multi-player stochastic games, where correlation signals are provided over time. In this s…