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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

The convergence of online learning algorithms in games under self-play is a fundamental question in game theory and machine learning. Among various notions of convergence, last-iterate convergence is particularly desirable, as it reflects…

Computer Science and Game Theory · Computer Science 2025-11-11 Yang Cai , Haipeng Luo , Chen-Yu Wei , Weiqiang Zheng

Consider a very simple class of (finite) games: after an initial move by nature, each player makes one move. Moreover, the players have common interests: at each node, all the players get the same payoff. We show that the problem of…

Computer Science and Game Theory · Computer Science 2007-05-23 Francis Chu , Joseph Y. Halpern

In this paper, we introduce and study a class of games called price-coupling games that arise in many scenarios, especially in the electricity industry. In a price-coupling game, there is a part of the objective function of a player which…

Optimization and Control · Mathematics 2019-01-08 Mathew P. Abraham , Ankur A. Kulkarni

It is well-known that for infinitely repeated games, there are computable strategies that have best responses, but no computable best responses. These results were originally proved for either specific games (e.g., Prisoner's dilemma), or…

Computer Science and Game Theory · Computer Science 2020-06-11 Jakub Dargaj , Jakob Grue Simonsen

This paper examines the convergence of no-regret learning in games with continuous action sets. For concreteness, we focus on learning via "dual averaging", a widely used class of no-regret learning schemes where players take small steps…

Optimization and Control · Mathematics 2018-01-17 Panayotis Mertikopoulos , Zhengyuan Zhou

We consider the classical problem of maximizing a monotone submodular function subject to a cardinality constraint, which, due to its numerous applications, has recently been studied in various computational models. We consider a clean…

Data Structures and Algorithms · Computer Science 2020-03-31 Moran Feldman , Ashkan Norouzi-Fard , Ola Svensson , Rico Zenklusen

We build a general theory for characterizing the computational complexity of motion planning of robot(s) through a graph of "gadgets", where each gadget has its own state defining a set of allowed traversals which in turn modify the…

Computational Complexity · Computer Science 2020-01-15 Erik D. Demaine , Dylan H. Hendrickson , Jayson Lynch

In many applications, we want to influence the decisions of independent agents by designing incentives for their actions. We revisit a fundamental problem in this area, called GAME IMPLEMENTATION: Given a game in standard form and a set of…

Computer Science and Game Theory · Computer Science 2022-12-02 Jiehua Chen , Sebastian Vincent Haydn , Negar Layegh Khavidaki , Sofia Simola , Manuel Sorge

We consider two-player games played in real time on game structures with clocks and parity objectives. The games are concurrent in that at each turn, both players independently propose a time delay and an action, and the action with the…

Logic in Computer Science · Computer Science 2008-07-09 Krishnendu Chatterjee , Thomas A. Henzinger , Vinayak Prabhu

In general, finite concurrent two-player reachability games are only determined in a weak sense: the supremum probability to win can be approached via stochastic strategies, but cannot be realized. We introduce a class of concurrent games…

Computer Science and Game Theory · Computer Science 2021-07-12 Benjamin Bordais , Patricia Bouyer , Stéphane Le Roux

We consider finite-state Markov decision processes with the combined Energy-MeanPayoff objective. The controller tries to avoid running out of energy while simultaneously attaining a strictly positive mean payoff in a second dimension. We…

Computer Science and Game Theory · Computer Science 2025-10-13 Mohan Dantam , Richard Mayr

We obtain global, non-asymptotic convergence guarantees for independent learning algorithms in competitive reinforcement learning settings with two agents (i.e., zero-sum stochastic games). We consider an episodic setting where in each…

Machine Learning · Computer Science 2021-01-13 Constantinos Daskalakis , Dylan J. Foster , Noah Golowich

We study the problem of deciding the winner of reachability switching games for zero-, one-, and two-player variants. Switching games provide a deterministic analogue of stochastic games. We show that the zero-player case is NL-hard, the…

Formal Languages and Automata Theory · Computer Science 2023-06-22 John Fearnley , Martin Gairing , Matthias Mnich , Rahul Savani

This paper is a twofold contribution. First, it contributes to the problem of enumerating some classes of simple games and in particular provides the number of weighted games with minimum and the number of weighted games for the dual class…

Combinatorics · Mathematics 2015-05-14 Josep Freixas , Sascha Kurz

One-counter MDPs (OC-MDPs) and one-counter simple stochastic games (OC-SSGs) are 1-player, and 2-player turn-based zero-sum, stochastic games played on the transition graph of classic one-counter automata (equivalently, pushdown automata…

Computer Science and Game Theory · Computer Science 2011-07-21 Tomáš Brázdil , Václav Brožek , Kousha Etessami , Antonín Kučera

Two-player quantitative zero-sum games provide a natural framework to synthesize controllers with performance guarantees for reactive systems within an uncontrollable environment. Classical settings include mean-payoff games, where the…

Logic in Computer Science · Computer Science 2015-09-25 Patricia Bouyer , Nicolas Markey , Mickael Randour , Kim G. Larsen , Simon Laursen

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 a game where one player selects a random function, and the other has to guess that function, and show that with high probability the second player can correctly guess most of the random function. We apply this analysis to…

Optimization and Control · Mathematics 2023-11-28 Catherine Rainer , Eilon Solan

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
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