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We consider zero-sum stochastic games with perfect information and finitely many states and actions. The payoff is computed by a function which associates to each infinite sequence of states and actions a real number. We prove that if the…

Computer Science and Game Theory · Computer Science 2022-03-29 Hugo Gimbert , Edon Kelmendi

We study finite-memory (FM) determinacy in games on finite graphs, a central question for applications in controller synthesis, as FM strategies correspond to implementable controllers. We establish general conditions under which FM…

Computer Science and Game Theory · Computer Science 2018-10-08 Stéphane Le Roux , Arno Pauly , Mickael Randour

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

Priced timed games are optimal-cost reachability games played between two players---the controller and the environment---by moving a token along the edges of infinite graphs of configurations of priced timed automata. The goal of the…

Logic in Computer Science · Computer Science 2015-07-22 Shibashis Guha , Shankara Narayanan Krishna , Lakshmi Manasa , Ashutosh Trivedi

Something is definitely wrong. If the game has a linear winning strategy, then it is tractable. What's going on? Well, we describe a two-person game which has a definite winner, that is, a player who can force a win in a finite number of…

Combinatorics · Mathematics 2016-09-07 Aviezri S. Fraenkel

We construct a statistical ensemble of games, where in each independent subensemble we have two players playing the same game. We derive the mean payoffs per move of the representative players of the game, and we evaluate all the…

Populations and Evolution · Quantitative Biology 2016-09-08 Rui Dilao , Joao Graciano

Mean Field Game (MFG) models implicitly assume "rational expectations", meaning that the heterogeneous agents being modeled correctly know all relevant transition probabilities for the complex system they inhabit. When there is common…

Analysis of PDEs · Mathematics 2026-02-26 Benjamin Moll , Lenya Ryzhik

We analyse the computational complexity of finding Nash equilibria in turn-based stochastic multiplayer games with omega-regular objectives. We show that restricting the search space to equilibria whose payoffs fall into a certain interval…

Computer Science and Game Theory · Computer Science 2015-07-01 Michael Ummels , Dominik Wojtczak

In budget-feasible mechanism design, a buyer wishes to procure a set of items of maximum value from self-interested players. We have a valuation function $v:2^U \to \mathbb{R}_+$, where $U$ is the set of all items, where $v(S)$ specifies…

Computer Science and Game Theory · Computer Science 2026-03-25 Rian Neogi , Kanstantsin Pashkovich , Chaitanya Swamy

We address the problem of existence and (non-)uniqueness of solutions $\big(c,u(\cdot),\mu\big)$ to ergodic mean-field games in the whole space $\mathbb{R}^{m}$ with unbounded and merely measurable data, and for non-separable Hamiltonian.…

Analysis of PDEs · Mathematics 2023-11-09 Hicham Kouhkouh

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

We propose a game-theoretic framework that incorporates both incomplete information and general ambiguity attitudes on factors external to all players. Our starting point is players' preferences on payoff-distribution vectors, essentially…

Economics · Quantitative Finance 2017-04-04 Jian Yang

Learning from repeated play in a fixed two-player zero-sum game is a classic problem in game theory and online learning. We consider a variant of this problem where the game payoff matrix changes over time, possibly in an adversarial…

Machine Learning · Computer Science 2022-02-01 Mengxiao Zhang , Peng Zhao , Haipeng Luo , Zhi-Hua Zhou

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

We consider two-player partial-observation stochastic games on finite-state graphs where player 1 has partial observation and player 2 has perfect observation. The winning condition we study are \omega-regular conditions specified as parity…

Logic in Computer Science · Computer Science 2014-01-15 Krishnendu Chatterjee , Laurent Doyen , Sumit Nain , Moshe Y. Vardi

Many high-stakes decision-making problems, such as those found within cybersecurity and economics, can be modeled as competitive resource allocation games. In these games, multiple players must allocate limited resources to overcome their…

Computer Science and Game Theory · Computer Science 2024-01-10 N'yoma Diamond , Fabricio Murai

We study 2-player turn-based perfect-information stochastic games with countably infinite state space. The players aim at maximizing/minimizing the probability of a given event (i.e., measurable set of infinite plays), such as reachability,…

Computer Science and Game Theory · Computer Science 2017-04-18 Stefan Kiefer , Richard Mayr , Mahsa Shirmohammadi , Dominik Wojtczak

We consider partially observable Markov decision processes (POMDPs) with limit-average payoff, where a reward value in the interval [0,1] is associated to every transition, and the payoff of an infinite path is the long-run average of the…

Artificial Intelligence · Computer Science 2014-08-12 Krishnendu Chatterjee , Martin Chmelik

We consider partially observable Markov decision processes (POMDPs) with limit-average payoff, where a reward value in the interval [0,1] is associated to every transition, and the payoff of an infinite path is the long-run average of the…

Artificial Intelligence · Computer Science 2013-08-23 Krishnendu Chatterjee , Martin Chmelík

We consider an assignment problem that has aspects of fair division as well as social choice. In particular, we investigate the problem of assigning a small subset from a set of indivisible items to multiple players so that the chosen…

Computer Science and Game Theory · Computer Science 2019-02-06 Warut Suksompong