3 papers
cs.LG2026
PAC Learning in Turn-Based Stochastic Games with Reachability Objectives: A Decentralized Private Approach via Expected Conditional Distance
Ali Asadi, Krishnendu Chatterjee, Pavol Kebis
Reachability is the most fundamental logical objective, yet it is notoriously difficult to learn in reinforcement learning settings: even for Markov decision processes, PAC learnin…
cs.GT2026
Generalized Bidding Games: Where Bidding and Stochastic Games Meet
Ali Asadi, Thomas A. Henzinger, Ehsan Kafshdar Goharshady +2
Two-player games on graphs are a classical framework for analyzing strategic decision making. In turn-based games, two players move a token along the edges of the graph, and the ri…
cs.FL2025
Quantitative Language Automata
Thomas A. Henzinger, Pavol Kebis, Nicolas Mazzocchi +1
A quantitative word automaton (QWA) defines a function from infinite words to values. For example, every infinite run of a limit-average QWA A obtains a mean payoff, and every word…