{"oa_version":"Published Version","type":"technical_report","citation":{"short":"K. Chatterjee, L. Doyen, H. Gimbert, Y. Oualhadj, Perfect-Information Stochastic Mean-Payoff Parity Games, IST Austria, 2013.","apa":"Chatterjee, K., Doyen, L., Gimbert, H., &#38; Oualhadj, Y. (2013). <i>Perfect-information stochastic mean-payoff parity games</i>. IST Austria. <a href=\"https://doi.org/10.15479/AT:IST-2013-128-v1-1\">https://doi.org/10.15479/AT:IST-2013-128-v1-1</a>","ista":"Chatterjee K, Doyen L, Gimbert H, Oualhadj Y. 2013. Perfect-information stochastic mean-payoff parity games, IST Austria, 22p.","ama":"Chatterjee K, Doyen L, Gimbert H, Oualhadj Y. <i>Perfect-Information Stochastic Mean-Payoff Parity Games</i>. IST Austria; 2013. doi:<a href=\"https://doi.org/10.15479/AT:IST-2013-128-v1-1\">10.15479/AT:IST-2013-128-v1-1</a>","chicago":"Chatterjee, Krishnendu, Laurent Doyen, Hugo Gimbert, and Youssouf Oualhadj. <i>Perfect-Information Stochastic Mean-Payoff Parity Games</i>. IST Austria, 2013. <a href=\"https://doi.org/10.15479/AT:IST-2013-128-v1-1\">https://doi.org/10.15479/AT:IST-2013-128-v1-1</a>.","ieee":"K. Chatterjee, L. Doyen, H. Gimbert, and Y. Oualhadj, <i>Perfect-information stochastic mean-payoff parity games</i>. IST Austria, 2013.","mla":"Chatterjee, Krishnendu, et al. <i>Perfect-Information Stochastic Mean-Payoff Parity Games</i>. IST Austria, 2013, doi:<a href=\"https://doi.org/10.15479/AT:IST-2013-128-v1-1\">10.15479/AT:IST-2013-128-v1-1</a>."},"publication_identifier":{"issn":["2664-1690"]},"doi":"10.15479/AT:IST-2013-128-v1-1","_id":"5405","has_accepted_license":"1","month":"07","title":"Perfect-information stochastic mean-payoff parity games","pubrep_id":"128","publication_status":"published","oa":1,"publisher":"IST Austria","related_material":{"record":[{"status":"public","id":"2212","relation":"later_version"}]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","page":"22","department":[{"_id":"KrCh"}],"language":[{"iso":"eng"}],"file_date_updated":"2020-07-14T12:46:45Z","author":[{"last_name":"Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","full_name":"Chatterjee, Krishnendu","orcid":"0000-0002-4561-241X","first_name":"Krishnendu"},{"first_name":"Laurent","full_name":"Doyen, Laurent","last_name":"Doyen"},{"full_name":"Gimbert, Hugo","first_name":"Hugo","last_name":"Gimbert"},{"last_name":"Oualhadj","first_name":"Youssouf","full_name":"Oualhadj, Youssouf"}],"day":"08","file":[{"content_type":"application/pdf","date_updated":"2020-07-14T12:46:45Z","file_name":"IST-2013-128-v1+1_full_stoch_mpp.pdf","date_created":"2018-12-12T11:53:54Z","file_size":387467,"relation":"main_file","access_level":"open_access","file_id":"5516","checksum":"ede787a10e74e4f7db302fab8f12f3ca","creator":"system"}],"ddc":["000","005","510"],"year":"2013","date_published":"2013-07-08T00:00:00Z","date_updated":"2023-02-23T10:33:08Z","alternative_title":["IST Austria Technical Report"],"status":"public","date_created":"2018-12-12T11:39:09Z","abstract":[{"text":"The theory of graph games is the foundation for modeling and synthesizing reactive processes. In the synthesis of stochastic processes, we use 2-1/2-player games where some transitions of the game graph are controlled by two adversarial players, the System and the Environment, and the other transitions are determined probabilistically. We consider 2-1/2-player games where the objective of the System is the conjunction of a qualitative objective (specified as a parity condition) and a quantitative objective (specified as a mean-payoff condition). We establish that the problem of deciding whether the System can ensure that the probability to satisfy the mean-payoff parity objective is at least a given threshold is in NP ∩ coNP, matching the best known bound in the special case of 2-player games (where all transitions are deterministic) with only parity objectives, or with only mean-payoff objectives. We present an algorithm running\r\nin time O(d · n^{2d}·MeanGame) to compute the set of almost-sure winning states from which the objective\r\ncan be ensured with probability 1, where n is the number of states of the game, d the number of priorities\r\nof the parity objective, and MeanGame is the complexity to compute the set of almost-sure winning states\r\nin 2-1/2-player mean-payoff games. Our results are useful in the synthesis of stochastic reactive systems\r\nwith both functional requirement (given as a qualitative objective) and performance requirement (given\r\nas a quantitative objective).","lang":"eng"}]}