Chatterjee, KrishnenduISTA ; Doyen, Laurent; Filiot, Emmanuel; Raskin, Jean
Two-player games on graphs provide the theoretical framework for many important problems such as reactive synthesis. While the traditional study of two-player zero-sum games has been extended to multi-player games with several notions of equilibria, they are decidable only for perfect-information games, whereas several applications require imperfect-information. In this paper we propose a new notion of equilibria, called doomsday equilibria, which is a strategy profile where all players satisfy their own objective, and if any coalition of players deviates and violates even one of the players' objective, then the objective of every player is violated. We present algorithms and complexity results for deciding the existence of doomsday equilibria for various classes of ω-regular objectives, both for imperfect-information games, and for perfect-information games. We provide optimal complexity bounds for imperfect-information games, and in most cases for perfect-information games.
Information and Computation
296 - 315
Chatterjee K, Doyen L, Filiot E, Raskin J. Doomsday equilibria for omega-regular games. Information and Computation. 2017;254:296-315. doi:10.1016/j.ic.2016.10.012
Chatterjee, K., Doyen, L., Filiot, E., & Raskin, J. (2017). Doomsday equilibria for omega-regular games. Information and Computation. Elsevier. https://doi.org/10.1016/j.ic.2016.10.012
Chatterjee, Krishnendu, Laurent Doyen, Emmanuel Filiot, and Jean Raskin. “Doomsday Equilibria for Omega-Regular Games.” Information and Computation. Elsevier, 2017. https://doi.org/10.1016/j.ic.2016.10.012.
K. Chatterjee, L. Doyen, E. Filiot, and J. Raskin, “Doomsday equilibria for omega-regular games,” Information and Computation, vol. 254. Elsevier, pp. 296–315, 2017.
Chatterjee K, Doyen L, Filiot E, Raskin J. 2017. Doomsday equilibria for omega-regular games. Information and Computation. 254, 296–315.
Chatterjee, Krishnendu, et al. “Doomsday Equilibria for Omega-Regular Games.” Information and Computation, vol. 254, Elsevier, 2017, pp. 296–315, doi:10.1016/j.ic.2016.10.012.
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