{"title":"Probabilistic systems with limsup and liminf objectives","quality_controlled":0,"status":"public","alternative_title":["LNCS"],"intvolume":" 5489","oa":1,"date_created":"2018-12-11T12:03:40Z","volume":5489,"publist_id":"2884","year":"2009","publisher":"Springer","date_published":"2009-12-15T00:00:00Z","publication_status":"published","extern":1,"citation":{"mla":"Chatterjee, Krishnendu, and Thomas A. Henzinger. Probabilistic Systems with Limsup and Liminf Objectives. Vol. 5489, Springer, 2009, pp. 32–45, doi:10.1007/978-3-642-03092-5_4.","ieee":"K. Chatterjee and T. A. Henzinger, “Probabilistic systems with limsup and liminf objectives,” presented at the ILC: Infinity in Logic and Computation, 2009, vol. 5489, pp. 32–45.","ista":"Chatterjee K, Henzinger TA. 2009. Probabilistic systems with limsup and liminf objectives. ILC: Infinity in Logic and Computation, LNCS, vol. 5489, 32–45.","chicago":"Chatterjee, Krishnendu, and Thomas A Henzinger. “Probabilistic Systems with Limsup and Liminf Objectives,” 5489:32–45. Springer, 2009. https://doi.org/10.1007/978-3-642-03092-5_4.","apa":"Chatterjee, K., & Henzinger, T. A. (2009). Probabilistic systems with limsup and liminf objectives (Vol. 5489, pp. 32–45). Presented at the ILC: Infinity in Logic and Computation, Springer. https://doi.org/10.1007/978-3-642-03092-5_4","ama":"Chatterjee K, Henzinger TA. Probabilistic systems with limsup and liminf objectives. In: Vol 5489. Springer; 2009:32-45. doi:10.1007/978-3-642-03092-5_4","short":"K. Chatterjee, T.A. Henzinger, in:, Springer, 2009, pp. 32–45."},"conference":{"name":"ILC: Infinity in Logic and Computation"},"_id":"3503","main_file_link":[{"url":"http://arxiv.org/abs/0809.1465","open_access":"1"}],"abstract":[{"lang":"eng","text":"We give polynomial-time algorithms for computing the values of Markov decision processes (MDPs) with limsup and liminf objectives. A real-valued reward is assigned to each state, and the value of an infinite path in the MDP is the limsup (resp. liminf) of all rewards along the path. The value of an MDP is the maximal expected value of an infinite path that can be achieved by resolving the decisions of the MDP. Using our result on MDPs, we show that turn-based stochastic games with limsup and liminf objectives can be solved in NP ∩ coNP. "}],"type":"conference","day":"15","author":[{"orcid":"0000-0002-4561-241X","first_name":"Krishnendu","last_name":"Chatterjee","full_name":"Krishnendu Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000−0002−2985−7724","first_name":"Thomas A","last_name":"Henzinger","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","full_name":"Thomas Henzinger"}],"doi":"10.1007/978-3-642-03092-5_4","page":"32 - 45","month":"12","date_updated":"2021-01-12T07:43:54Z"}