Mean-Payoff Parity Games

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 realvalued 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.

• Type: Conference
• Year: 2005
• Where: LICS
• Authors: Krishnendu Chatterjee, Thomas A. Henzinger, Marcin Jurdzinski
• Keywords: Computer Science, LICS 2005, Mean-payoff Parity Games, Quantitative Component, Quantitative Objectives