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Related papers: Repeated Games with Tail-Measurable Payoffs

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In this paper, we study games with continuous action spaces and non-linear payoff functions. Our key insight is that Lipschitz continuity of the payoff function allows us to provide algorithms for finding approximate equilibria in these…

Computer Science and Game Theory · Computer Science 2016-03-31 Argyrios Deligkas , John Fearnley , Paul Spirakis

We study nondeterministic strategies in parity games with the aim of computing a most permissive winning strategy. Following earlier work, we measure permissiveness in terms of the average number/weight of transitions blocked by the…

Logic in Computer Science · Computer Science 2013-01-14 Patricia Bouyer , Nicolas Markey , Jörg Olschewski , Michael Ummels

In game theory, the concept of Nash equilibrium reflects the collective stability of some individual strategies chosen by selfish agents. The concept pertains to different classes of games, e.g. the sequential games, where the agents play…

Logic · Mathematics 2015-07-01 Stephane Le Roux

A Bayesian game is said to have nested information if the players are ordered, and each player knows the types of all players that follow her in that order. We prove that all multiplayer Bayesian games with finite actions spaces, bounded…

Probability · Mathematics 2025-02-24 Royi Jacobovic , John Yehuda Levy , Eilon Solan

We consider a finite horizon repeated game with $N$ selfish players who observe their types privately and take actions, which are publicly observed. Their actions and types jointly determine their instantaneous rewards. In each period,…

Computer Science and Game Theory · Computer Science 2019-05-17 Deepanshu Vasal

In two-player games on graphs, the players move a token through a graph to produce an infinite path, which determines the winner or payoff of the game. Such games are central in formal verification since they model the interaction between a…

Computer Science and Game Theory · Computer Science 2020-01-28 Guy Avni , Thomas A. Henzinger , Rasmus Ibsen-Jensen

In a two-player zero-sum graph game the players move a token throughout a graph to produce an infinite path, which determines the winner or payoff of the game. Traditionally, the players alternate turns in moving the token. In {\em bidding…

Theoretical Economics · Economics 2020-12-22 Guy Avni , Ismaël Jecker , Đorđe Žikelić

In an $\epsilon$-Nash equilibrium, a player can gain at most $\epsilon$ by unilaterally changing his behaviour. For two-player (bimatrix) games with payoffs in $[0,1]$, the best-known$\epsilon$ achievable in polynomial time is 0.3393. In…

Computer Science and Game Theory · Computer Science 2014-10-02 Argyrios Deligkas , John Fearnley , Rahul Savani , Paul Spirakis

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

Pursuit-Evasion Games (in discrete time) are stochastic games with nonnegative daily payoffs, with the final payoff being the cumulative sum of payoffs during the game. We show that such games admit a value even in the presence of…

Probability · Mathematics 2007-08-21 Ori Gurel-Gurevich

We show that, for a continuous set of entangled four-partite states, the task of maximizing the payoff in the symmetric-strategy four-player quantum Minority game is equivalent to maximizing the violation of a four-particle Bell inequality…

We use techniques from the statistical mechanics of disordered systems to analyse the properties of Nash equilibria of bimatrix games with large random payoff matrices. By means of an annealed bound, we calculate their number and analyse…

Disordered Systems and Neural Networks · Physics 2009-10-31 Johannes Berg , Martin Weigt

In this paper, we study the problem of learning in quantum games - and other classes of semidefinite games - with scalar, payoff-based feedback. For concreteness, we focus on the widely used matrix multiplicative weights (MMW) algorithm…

Computer Science and Game Theory · Computer Science 2023-11-07 Kyriakos Lotidis , Panayotis Mertikopoulos , Nicholas Bambos , Jose Blanchet

Imitation is simple behavior which uses successful actions of others in order to deal with one's own problems. Because success of imitation generally depends on whether profit of an imitating agent coincides with those of other agents or…

Physics and Society · Physics 2023-01-23 Masahiko Ueda

We study multi-objective reinforcement learning (RL) where an agent's reward is represented as a vector. In settings where an agent competes against opponents, its performance is measured by the distance of its average return vector to a…

Machine Learning · Computer Science 2021-02-08 Tiancheng Yu , Yi Tian , Jingzhao Zhang , Suvrit Sra

In this paper, we introduce the concept of infinitely split Nash equilibrium in repeated games in which the profile sets are chain-complete posets. Then by using a fixed point theorem on posets in [8], we prove an existence theorem. As an…

Optimization and Control · Mathematics 2017-12-25 Jinlu Li

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 study a multi-player one-round game termed Stackelberg Network Pricing Game, in which a leader can set prices for a subset of $m$ priceable edges in a graph. The other edges have a fixed cost. Based on the leader's decision one or more…

Data Structures and Algorithms · Computer Science 2008-02-21 Patrick Briest , Martin Hoefer , Piotr Krysta

In this paper, we study two-player zero-sum turn-based games played on a finite multidimensional weighted graph. In recent papers all dimensions use the same measure, whereas here we allow to combine different measures. Such heterogeneous…

Computer Science and Game Theory · Computer Science 2016-06-22 Véronique Bruyère , Quentin Hautem , Jean-François Raskin

We study best-response type learning dynamics for zero-sum polymatrix games under two information settings. The two settings are distinguished by the type of information that each player has about the game and their opponents' strategy. The…

Optimization and Control · Mathematics 2025-08-13 Fathima Zarin Faizal , Asuman Ozdaglar , Martin J. Wainwright