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In this paper, we aim to develop distributed continuous-time algorithms over directed graphs to seek the Nash equilibrium in a noncooperative game. Motivated by the recent consensus-based designs, we present a distributed algorithm with a…

Optimization and Control · Mathematics 2022-04-19 Yutao Tang , Peng Yi , Yanqiong Zhang , Dawei Liu

Network congestion games are a convenient model for reasoning about routing problems in a network: agents have to move from a source to a target vertex while avoiding congestion, measured as a cost depending on the number of players using…

Computer Science and Game Theory · Computer Science 2022-07-05 Aline Goeminne , Nicolas Markey , Ocan Sankur

Generalized Nash equilibrium problems with mixed-integer variables constitute an important class of games in which each player solves a mixed-integer optimization problem, where both the objective and the feasible set is parameterized by…

Computer Science and Game Theory · Computer Science 2025-11-06 Aloïs Duguet , Tobias Harks , Martin Schmidt , Julian Schwarz

We investigate Nash equilibrium learning in a competitive Markov Game (MG) environment, where multiple agents compete, and multiple Nash equilibria can exist. In particular, for an oligopolistic dynamic pricing environment, exact Nash…

Computer Science and Game Theory · Computer Science 2024-03-05 Larkin Liu

We investigate the complexity of bounding the uncertainty of graphical games, and we provide new insight into the intrinsic difficulty of computing Nash equilibria. In particular, we show that, if one adds very simple and natural additional…

Computer Science and Game Theory · Computer Science 2012-07-09 Gianluigi Greco , Francesco Scarcello

We present a deterministic polynomial-time algorithm for computing $d^{d+o(d)}$-approximate (pure) Nash equilibria in (proportional sharing) weighted congestion games with polynomial cost functions of degree at most $d$. This is an…

Computer Science and Game Theory · Computer Science 2020-11-26 Yiannis Giannakopoulos , Georgy Noarov , Andreas S. Schulz

We explore the use of policy approximations to reduce the computational cost of learning Nash equilibria in zero-sum stochastic games. We propose a new Q-learning type algorithm that uses a sequence of entropy-regularized soft policies to…

Machine Learning · Computer Science 2021-06-29 Yue Guan , Qifan Zhang , Panagiotis Tsiotras

To verify the robustness of a program or protocol, it is common in the computer science community to rely on the theoretical framework of game theory. In particular, if one seeks to enforce a desired property, or specification, despite an…

Computer Science and Game Theory · Computer Science 2026-05-20 Léonard Brice

We compute a parametric description of the totally mixed Nash equilibria of a generic game in normal form with pre-fixed structure. Using this representation, we show conditions under which a game has the maximum possible number of this…

Algebraic Geometry · Mathematics 2007-05-23 G. Jeronimo , D. Perrucci , J. Sabia

The rank of a bimatrix game (A,B) is defined as rank(A+B). Computing a Nash equilibrium (NE) of a rank-$0$, i.e., zero-sum game is equivalent to linear programming (von Neumann'28, Dantzig'51). In 2005, Kannan and Theobald gave an FPTAS for…

Computer Science and Game Theory · Computer Science 2014-03-25 Ruta Mehta

Nash equilibria are crucial for understanding game behavior and systems in economics, physics, biology, and computer science. A significant application arises from the connection between Nash equilibria and optimization problems . However,…

Quantum Physics · Physics 2025-11-14 Giovanni Ferrannini , Dario di Gregorio , Federico Fissore

We present multilinear and mixed-integer multilinear programs to find a Nash equilibrium in multi-player noncooperative games. We compare the formulations to common algorithms in Gambit, and conclude that a multilinear feasibility program…

Optimization and Control · Mathematics 2024-03-27 Miriam Fischer , Akshay Gupte

An open problem in linear quadratic (LQ) games has been characterizing the Nash equilibria. This problem has renewed relevance given the surge of work on understanding the convergence of learning algorithms in dynamic games. This paper…

Computer Science and Game Theory · Computer Science 2025-04-18 Giulio Salizzoni , Reda Ouhamma , Maryam Kamgarpour

We consider two classes of constrained finite state-action stochastic games. First, we consider a two player nonzero sum single controller constrained stochastic game with both average and discounted cost criterion. We consider the same…

Optimization and Control · Mathematics 2012-06-11 Vikas Vikram Singh , N. Hemachandra

We study strategic games on weighted directed graphs, in which the payoff of a player is defined as the sum of the weights on the edges from players who chose the same strategy, augmented by a fixed non-negative integer bonus for picking a…

Computer Science and Game Theory · Computer Science 2021-03-15 Krzysztof R. Apt , Sunil Simon , Dominik Wojtczak

We study the structure of the set of equilibrium payoffs in finite games, both for Nash equilibrium and correlated equilibrium. A nonempty subset of R^2 is shown to be the set of Nash equilibrium payoffs of a bimatrix game if and only if it…

Optimization and Control · Mathematics 2009-02-17 Ehud Lehrer , Eilon Solan , Yannick Viossat

We consider an algorithmic framework for two-player non-zero-sum semidefinite games, where each player's strategy is a positive semidefinite matrix with trace one. We formulate the computation of Nash equilibria in such games as…

Optimization and Control · Mathematics 2025-06-16 Constantin Ickstadt , Thorsten Theobald , Elias Tsigaridas , Antonios Varvitsiotis

Continuous games are multiplayer games in which strategy sets are compact and utility functions are continuous. These games typically have a highly complicated structure of Nash equilibria, and numerical methods for the equilibrium…

Computer Science and Game Theory · Computer Science 2022-07-12 T. Kroupa , T. Votroubek

Computing an equilibrium in congestion games can be challenging when the number of players is large. Yet, it is a problem to be addressed in practice, for instance to forecast the state of the system and be able to control it. In this work,…

Computer Science and Game Theory · Computer Science 2018-10-04 Cheng Wan , Paulin Jacquot , Olivier Beaude , Nadia Oudjane

This paper considers the problem of designing optimal algorithms for reinforcement learning in two-player zero-sum games. We focus on self-play algorithms which learn the optimal policy by playing against itself without any direct…

Machine Learning · Computer Science 2020-07-15 Yu Bai , Chi Jin , Tiancheng Yu
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