Titre:
Computing Optimal Strategies for Markov Decision Processes with Parity and Positive-Average Conditions
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Date | 2011-02-24 14:00-15:00 |
Nom | Computing Optimal Strategies for Markov Decision Processes with Parity and Positive-Average Conditions |
Description | We study Markov decision processes (one-player stochastic games) equipped with parity and positive-average conditions. In these games, the goal of the player is to maximize the probability that both the parity and the positive-average conditions are fulfilled. We show that the values of these games are computable. We also show that optimal strategies exist, require only finite memory and can be effectively computed. |
Lieu | Amphi |
Contact | Youssouf Oualhadj |
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