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We consider two-person zero-sum stochastic mean payoff games with perfect information, or BWR-games, given by a digraph $G = (V, E)$, with local rewards $r: E \to \ZZ$, and three types of positions: black $V_B$, white $V_W$, and random…

Computer Science and Game Theory · Computer Science 2017-03-27 Endre Boros , Khaled Elbassioni , Vladimir Gurvich , Kazuhisa Makino

In this work we offer an $O(|V|^2 |E|\, W)$ pseudo-polynomial time deterministic algorithm for solving the Value Problem and Optimal Strategy Synthesis in Mean Payoff Games. This improves by a factor $\log(|V|\, W)$ the best previously…

Data Structures and Algorithms · Computer Science 2016-04-26 Carlo Comin , Romeo Rizzi

We consider some well-known families of two-player, zero-sum, perfect information games that can be viewed as special cases of Shapley's stochastic games. We show that the following tasks are polynomial time equivalent: - Solving simple…

Computer Science and Game Theory · Computer Science 2008-12-03 Vladimir Gurvich , Peter Bro Miltersen

In a mean-payoff parity game, one of the two players aims both to achieve a qualitative parity objective and to minimize a quantitative long-term average of payoffs (aka. mean payoff). The game is zero-sum and hence the aim of the other…

Computer Science and Game Theory · Computer Science 2020-01-15 Laure Daviaud , Marcin Jurdzinski , Ranko Lazic

Stochastic games are an important class of problems that generalize Markov decision processes to game theoretic scenarios. We consider finite state two-player zero-sum stochastic games over an infinite time horizon with discounted rewards.…

Optimization and Control · Mathematics 2008-06-17 Parikshit Shah , Pablo A. Parrilo

Quantitative games are two-player zero-sum games played on directed weighted graphs. Total-payoff games (that can be seen as a refinement of the well-studied mean-payoff games) are the variant where the payoff of a play is computed as the…

Computer Science and Game Theory · Computer Science 2015-07-15 Thomas Brihaye , Gilles Geeraerts , Axel Haddad , Benjamin Monmege

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

We develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to…

Computer Science and Game Theory · Computer Science 2024-11-12 Xavier Allamigeon , Stéphane Gaubert , Ricardo D. Katz , Mateusz Skomra

We consider discrete time partially observable zero-sum stochastic game with average payoff criterion. We study the game using an equivalent completely observable game. We show that the game has a value and also we come up with a pair of…

Optimization and Control · Mathematics 2014-09-16 Subhamay Saha

Recent results of Ye and Hansen, Miltersen and Zwick show that policy iteration for one or two player (perfect information) zero-sum stochastic games, restricted to instances with a fixed discount rate, is strongly polynomial. We show that…

Optimization and Control · Mathematics 2013-10-21 Marianne Akian , Stéphane Gaubert

Motivated by the sequence form formulation of Koller et al. (GEB'96), this paper defines {\em bilinear games}, and proposes efficient algorithms for its rank based subclasses. Bilinear games are two-player non-cooperative single-shot games…

Computer Science and Game Theory · Computer Science 2011-09-29 Jugal Garg , Albert Xin Jiang , Ruta Mehta

Two-player complete-information game trees are perhaps the simplest possible setting for studying general-sum games and the computational problem of finding equilibria. These games admit a simple bottom-up algorithm for finding subgame…

Computer Science and Game Theory · Computer Science 2012-07-02 Michael L. Littman , Nishkam Ravi , Arjun Talwar , Martin Zinkevich

We examine perfect information stochastic mean-payoff games - a class of games containing as special sub-classes the usual mean-payoff games and parity games. We show that deterministic memoryless strategies that are optimal for discounted…

Computer Science and Game Theory · Computer Science 2010-06-09 Hugo Gimbert , Wiesław Zielonka

We consider two-player games played on weighted directed graphs with mean-payoff and total-payoff objectives, two classical quantitative objectives. While for single-dimensional games the complexity and memory bounds for both objectives…

Computer Science and Game Theory · Computer Science 2014-11-04 Krishnendu Chatterjee , Laurent Doyen , Mickael Randour , Jean-François Raskin

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

We show that an N-person non-cooperative semi-Markov game under limiting ratio average pay-off has a pure semi-stationary Nash equilibrium. In an earlier paper, the zero-sum two person case has been dealt with. The proof follows by reducing…

Computer Science and Game Theory · Computer Science 2024-02-27 K. G. Bakshi , S. Sinha

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 consider concurrent mean-payoff games, a very well-studied class of two-player (player 1 vs player 2) zero-sum games on finite-state graphs where every transition is assigned a reward between 0 and 1, and the payoff function is the…

Computer Science and Game Theory · Computer Science 2014-10-02 Krishnendu Chatterjee , Rasmus Ibsen-Jensen

A long-standing open problem in algorithmic game theory asks whether or not there is a polynomial time algorithm to compute a Nash equilibrium in a random bimatrix game. We study random win-lose games, where the entries of the $n\times n$…

Computer Science and Game Theory · Computer Science 2025-10-16 Andrea Collevecchio , Gabor Lugosi , Adrian Vetta , Rui-Ray Zhang

The solution to a Nash or a nonsymmetric bargaining game is obtained by maximizing a concave function over a convex set, i.e., it is the solution to a convex program. We show that each 2-player game whose convex program has linear…

Computer Science and Game Theory · Computer Science 2015-05-13 Vijay V. Vazirani
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