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Stopping Criteria for Value Iteration on Stochastic Games with Quantitative Objectives

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KŘETÍNSKÝ Jan MEGGENDORFER Tobias WEININGER Maximilian

Rok publikování 2023
Druh Článek ve sborníku
Konference 2023 38TH ANNUAL ACM/IEEE SYMPOSIUM ON LOGIC IN COMPUTER SCIENCE, LICS
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
Doi http://dx.doi.org/10.1109/LICS56636.2023.10175771
Klíčová slova Stochastic games; value iteration
Popis A classic solution technique for Markov decision processes (MDP) and stochastic games (SG) is value iteration (VI). Due to its good practical performance, this approximative approach is typically preferred over exact techniques, even though no practical bounds on the imprecision of the result could be given until recently. As a consequence, even the most used model checkers could return arbitrarily wrong results. Over the past decade, different works derived stopping criteria, indicating when the precision reaches the desired level, for various settings, in particular MDP with reachability, total reward, and mean payoff, and SG with reachability.

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