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Evolutionary game theory is a powerful mathematical framework to study how intelligent individuals adjust their strategies in collective interactions. It has been widely believed that it is impossible to unilaterally control players'…

Optimization and Control · Mathematics 2021-08-31 Renfei Tan , Qi Su , Bin Wu , Long Wang

Traditional solvable game theory and mean-field-type game theory (risk-aware games) predominantly focus on quadratic costs due to their analytical tractability. Nevertheless, they often fail to capture critical non-linearities inherent in…

Optimization and Control · Mathematics 2025-05-09 Julian Barreiro-Gomez , Tyrone E. Duncan , Bozenna Pasik-Duncan , Hamidou Tembine

The window mechanism, introduced by Chatterjee et al. for mean-payoff and total-payoff objectives in two-player turn-based games on graphs, refines long-term objectives with time bounds. This mechanism has proven useful in a variety of…

Computer Science and Game Theory · Computer Science 2022-05-10 James C. A. Main , Mickael Randour , Jeremy Sproston

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

We consider two-player stochastic games played on a finite graph for infinitely many rounds. Stochastic games generalize both Markov decision processes (MDP) by adding an adversary player, and two-player deterministic games by adding…

Computer Science and Game Theory · Computer Science 2022-02-28 Laurent Doyen

In two-player games on graph, the players construct an infinite path through the game graph and get a reward computed by a payoff function over infinite paths. Over weighted graphs, the typical and most studied payoff functions compute the…

Computer Science and Game Theory · Computer Science 2011-04-19 Krishnendu Chatterjee , Laurent Doyen , Rohit Singh

We study countably infinite Markov decision processes (MDPs) with real-valued transition rewards. Every infinite run induces the following sequences of payoffs: 1. Point payoff (the sequence of directly seen transition rewards), 2. Total…

Artificial Intelligence · Computer Science 2021-07-13 Richard Mayr , Eric Munday

In this paper, we study nonzero-sum separable games, which are continuous games whose payoffs take a sum-of-products form. Included in this subclass are all finite games and polynomial games. We investigate the structure of equilibria in…

Computer Science and Game Theory · Computer Science 2010-04-26 Noah D. Stein , Asuman Ozdaglar , Pablo A. Parrilo

The long-run average payoff per transition (mean payoff) is the main tool for specifying the performance and dependability properties of discrete systems. The problem of constructing a controller (strategy) simultaneously optimizing several…

Artificial Intelligence · Computer Science 2024-12-19 David Klaška , Antonín Kučera , Vojtěch Kůr , Vít Musil , Vojtěch Řehák

Reachability games are two-player games played on a graph, where the objective of $\texttt{REACH}$ player is to reach the target set whereas the objective of $\texttt{SAFE}$ player is to stay away from the target set. Reachability games…

Artificial Intelligence · Computer Science 2026-05-12 Krishnendu Chatterjee , Ehsan Kafshdar Goharshady , Mehrdad Karrabi , Maximilian Seeliger , Đorđe Žikelić

In this paper, we resolve the computational complexity of a number of outstanding open problems with practical applications. Here is the list of problems we show to be PPAD-complete, along with the domains of practical significance:…

Computational Complexity · Computer Science 2009-04-10 Shiva Kintali , Laura J. Poplawski , Rajmohan Rajaraman , Ravi Sundaram , Shang-Hua Teng

Energy parity games are infinite two-player turn-based games played on weighted graphs. The objective of the game combines a (qualitative) parity condition with the (quantitative) requirement that the sum of the weights (i.e., the level of…

Logic in Computer Science · Computer Science 2012-04-04 Krishnendu Chatterjee , Laurent Doyen

We formulate a class of mean field games on a finite state space with variational principles resembling those in continuous-state mean field games. We construct a controlled continuity equation featuring a nonlinear activation function on…

Optimization and Control · Mathematics 2023-10-10 Yuan Gao , Wuchen Li , Jian-Guo Liu

We continue the investigation of finite-duration variants of infinite-duration games by extending known results for games played on finite graphs to those played on infinite ones. In particular, we establish an equivalence between pushdown…

Computer Science and Game Theory · Computer Science 2012-10-10 Wladimir Fridman , Martin Zimmermann

We study Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) functions. We consider two different objectives, namely, expectation and satisfaction objectives. Given an MDP with k limit-average functions, in the…

Computer Science and Game Theory · Computer Science 2015-07-01 Tomáš Brázdil , Václav Brožek , Krishnendu Chatterjee , Vojtěch Forejt , Antonín Kučera

Energy games are a well-studied class of 2-player turn-based games on a finite graph where transitions are labeled with integer vectors which represent changes in a multidimensional resource (the energy). One player tries to keep the…

Computer Science and Game Theory · Computer Science 2014-05-06 Parosh Aziz Abdulla , Mohamed Faouzi Atig , Piotr Hofman , Richard Mayr , K. Narayan Kumar , Patrick Totzke

Games on graphs provide a natural and powerful model for reactive systems. In this paper, we consider generalized reachability objectives, defined as conjunctions of reachability objectives. We first prove that deciding the winner in such…

Computational Complexity · Computer Science 2012-02-06 Nathanaël Fijalkow , Florian Horn

We consider Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) objectives. There exist two different views: (i) the expectation semantics, where the goal is to optimize the expected mean-payoff objective, and (ii)…

Logic in Computer Science · Computer Science 2019-03-14 Krishnendu Chatterjee , Zuzana Křetínská , Jan Křetínský

Energy games belong to a class of turn-based two-player infinite-duration games}played on a weighted directed graph. It is one of the rare and intriguing combinatorial problems that lie in ${\sf NP} \cap {\sf co\mbox{-}NP}$, but are not…

Data Structures and Algorithms · Computer Science 2018-03-02 Krishnendu Chatterjee , Monika Henzinger , Sebastian Krinninger , Danupon Nanongkai

We study the problem of finding equilibrium strategies in multi-agent games with incomplete payoff information, where the payoff matrices are only known to the players up to some bounded uncertainty sets. In such games, an ex-post…

Computer Science and Game Theory · Computer Science 2020-07-14 Wenshuo Guo , Mihaela Curmei , Serena Wang , Benjamin Recht , Michael I. Jordan