{"date_created":"2018-12-11T12:09:27Z","title":"Mean-payoff parity games","page":"178 - 187","date_published":"2005-09-19T00:00:00Z","author":[{"id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","last_name":"Chatterjee","first_name":"Krishnendu","orcid":"0000-0002-4561-241X","full_name":"Krishnendu Chatterjee"},{"full_name":"Thomas Henzinger","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","last_name":"Henzinger","first_name":"Thomas A","orcid":"0000−0002−2985−7724"},{"last_name":"Jurdziński","first_name":"Marcin","full_name":"Jurdziński, Marcin"}],"month":"09","citation":{"ama":"Chatterjee K, Henzinger TA, Jurdziński M. Mean-payoff parity games. In: IEEE; 2005:178-187. doi:<a href=\"https://doi.org/10.1109/LICS.2005.26\">10.1109/LICS.2005.26</a>","chicago":"Chatterjee, Krishnendu, Thomas A Henzinger, and Marcin Jurdziński. “Mean-Payoff Parity Games,” 178–87. IEEE, 2005. <a href=\"https://doi.org/10.1109/LICS.2005.26\">https://doi.org/10.1109/LICS.2005.26</a>.","mla":"Chatterjee, Krishnendu, et al. <i>Mean-Payoff Parity Games</i>. IEEE, 2005, pp. 178–87, doi:<a href=\"https://doi.org/10.1109/LICS.2005.26\">10.1109/LICS.2005.26</a>.","apa":"Chatterjee, K., Henzinger, T. A., &#38; Jurdziński, M. (2005). Mean-payoff parity games (pp. 178–187). Presented at the LICS: Logic in Computer Science, IEEE. <a href=\"https://doi.org/10.1109/LICS.2005.26\">https://doi.org/10.1109/LICS.2005.26</a>","ista":"Chatterjee K, Henzinger TA, Jurdziński M. 2005. Mean-payoff parity games. LICS: Logic in Computer Science, 178–187.","ieee":"K. Chatterjee, T. A. Henzinger, and M. Jurdziński, “Mean-payoff parity games,” presented at the LICS: Logic in Computer Science, 2005, pp. 178–187.","short":"K. Chatterjee, T.A. Henzinger, M. Jurdziński, in:, IEEE, 2005, pp. 178–187."},"publisher":"IEEE","abstract":[{"lang":"eng","text":"Games played on graphs may have qualitative objectives, such as the satisfaction of an ω-regular property, or quantitative objectives, such as the optimization of a real-valued reward. When games are used to model reactive systems with both fairness assumptions and quantitative (e.g., resource) constraints, then the corresponding objective combines both a qualitative and a quantitative component. In a general case of interest, the qualitative component is a parity condition and the quantitative component is a mean-payoff reward. We study and solve such mean-payoff parity games. We also prove some interesting facts about mean-payoff parity games which distinguish them both from mean-payoff and from parity games. In particular, we show that optimal strategies exist in mean-payoff parity games, but they may require infinite memory."}],"quality_controlled":0,"publication_status":"published","publist_id":"159","day":"19","date_updated":"2021-01-12T07:59:39Z","status":"public","year":"2005","_id":"4554","extern":1,"doi":"10.1109/LICS.2005.26","type":"conference","conference":{"name":"LICS: Logic in Computer Science"}}