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While discounted payoff games and classic games that reduce to them, like parity and mean-payoff games, are symmetric, their solutions are not. We have taken a fresh view on the constraints that optimal solutions need to satisfy, and…

Data Structures and Algorithms · Computer Science 2023-10-03 Daniele Dell'Erba , Arthur Dumas , Sven Schewe

Symmetry is inherent in the definition of most of the two-player zero-sum games, including parity, mean-payoff, and discounted-payoff games. It is therefore quite surprising that no symmetric analysis techniques for these games exist. We…

Computer Science and Game Theory · Computer Science 2015-01-27 Sven Schewe , Ashutosh Trivedi , Thomas Varghese

This paper introduces alignment games, a new class of zero-sum games modeling strategic interventions where effectiveness depends on alignment with an underlying hidden state. Motivated by operational problems in medical diagnostics,…

Optimization and Control · Mathematics 2025-09-08 Pedro Cesar Lopes Gerum , Thomas Lidbetter

Strategy improvement is a widely-used and well-studied class of algorithms for solving graph-based infinite games. These algorithms are parameterized by a switching rule, and one of the most natural rules is "all switches" which switches as…

Data Structures and Algorithms · Computer Science 2023-06-22 John Fearnley , Rahul Savani

The strategy improvement algorithm for mean payoff games and parity games is a local improvement algorithm, just like the simplex algorithm for linear programs. Their similarity has turned out very useful: many lower bounds on running time…

Computer Science and Game Theory · Computer Science 2025-09-22 Matthew Maat

Symmetric strategy improvement is an algorithm introduced by Schewe et al. (ICALP 2015) that can be used to solve two-player games on directed graphs such as parity games and mean payoff games. In contrast to the usual well-known strategy…

Computer Science and Game Theory · Computer Science 2023-09-06 Tom van Dijk , Georg Loho , Matthew Maat

We study two-player zero-sum concurrent stochastic games with finite state and action space played for an infinite number of steps. In every step, the two players simultaneously and independently choose an action. Given the current state…

Computer Science and Game Theory · Computer Science 2024-10-10 Ali Asadi , Krishnendu Chatterjee , Raimundo Saona , Jakub Svoboda

This paper examines multiplayer symmetric constant-sum games with more than two players in a competitive setting, including examples like Mahjong, Poker, and various board and video games. In contrast to two-player zero-sum games,…

Machine Learning · Computer Science 2024-10-04 Jiawei Ge , Yuanhao Wang , Wenzhe Li , Chi Jin

Graph games provide the foundation for modeling and synthesis of reactive processes. Such games are played over graphs where the vertices are controlled by two adversarial players. We consider graph games where the objective of the first…

Computer Science and Game Theory · Computer Science 2017-06-21 Krishnendu Chatterjee , Monika Henzinger , Alexander Svozil

In mean-payoff games, the objective of the protagonist is to ensure that the limit average of an infinite sequence of numeric weights is nonnegative. In energy games, the objective is to ensure that the running sum of weights is always…

Computer Science and Game Theory · Computer Science 2012-09-17 Yaron Velner , Krishnendu Chatterjee , Laurent Doyen , Thomas A. Henzinger , Alexander Rabinovich , Jean-Francois Raskin

Classical objectives in two-player zero-sum games played on graphs often deal with limit behaviors of infinite plays: e.g., mean-payoff and total-payoff in the quantitative setting, or parity in the qualitative one (a canonical way to…

Logic in Computer Science · Computer Science 2016-09-15 Véronique Bruyère , Quentin Hautem , Mickael Randour

Solutions to multi-objective optimization problems can generally not be compared or ordered, due to the lack of orderability of the single objectives. Furthermore, decision-makers are often made to believe that scaled objectives can be…

Optimization and Control · Mathematics 2022-05-31 Sebastian Hönel , Welf Löwe

This paper proposes an asymmetric perturbation technique for solving bilinear saddle-point optimization problems, commonly arising in minimax problems, game theory, and constrained optimization. Perturbing payoffs or values is known to be…

Optimization and Control · Mathematics 2026-02-16 Kenshi Abe , Mitsuki Sakamoto , Kaito Ariu , Atsushi Iwasaki

We study stochastic two-player turn-based games in which the objective of one player is to ensure several infinite-horizon total reward objectives, while the other player attempts to spoil at least one of the objectives. The games have…

Computer Science and Game Theory · Computer Science 2016-05-13 Romain Brenguier , Vojtěch Forejt

In a multiobjective optimization problem a solution is called Pareto-optimal if no criterion can be improved without deteriorating at least one of the other criteria. Computing the set of all Pareto-optimal solutions is a common task in…

Data Structures and Algorithms · Computer Science 2020-10-22 Heiko Röglin

Mean-payoff games (MPGs) are infinite duration two-player zero-sum games played on weighted graphs. Under the hypothesis of perfect information, they admit memoryless optimal strategies for both players and can be solved in…

Logic in Computer Science · Computer Science 2015-04-14 Paul Hunter , Guillermo A. Pérez , Jean-François Raskin

Classical objectives in two-player zero-sum games played on graphs often deal with limit behaviors of infinite plays: e.g., mean-payoff and total-payoff in the quantitative setting, or parity in the qualitative one (a canonical way to…

Logic in Computer Science · Computer Science 2016-09-21 Véronique Bruyère , Quentin Hautem , Mickael Randour

Traditionally quantitative games such as mean-payoff games and discount sum games have two players -- one trying to maximize the payoff, the other trying to minimize it. The associated decision problem, "Can Eve (the maximizer) achieve, for…

Logic in Computer Science · Computer Science 2014-04-21 Paul Hunter , Jean-François Raskin

In a multi-objective game, each individual's payoff is a \emph{vector-valued} function of everyone's actions. Under such vectorial payoffs, Pareto-efficiency is used to formulate each individual's best-response condition, inducing…

Computer Science and Game Theory · Computer Science 2018-09-14 Anisse Ismaili

Nonzero-sum stochastic differential games with impulse controls offer a realistic and far-reaching modelling framework for applications within finance, energy markets, and other areas, but the difficulty in solving such problems has…

Numerical Analysis · Mathematics 2020-06-29 Diego Zabaljauregui
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