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We revisit the complexity of deciding, given a {\it bimatrix game,} whether it has a {\it Nash equilibrium} with certain natural properties; such decision problems were early known to be ${\mathcal{NP}}$-hard~\cite{GZ89}. We show that…

Computational Complexity · Computer Science 2019-07-25 Vittorio Bilò , Marios Mavronicolas

This paper considers a class of reinforcement-based learning (namely, perturbed learning automata) and provides a stochastic-stability analysis in repeatedly-played, positive-utility, finite strategic-form games. Prior work in this class of…

Computer Science and Game Theory · Computer Science 2019-01-29 Georgios C. Chasparis

We analyze the stability of a nonlinear dynamical model describing the noncooperative strategic interactions among the agents of a finite collection of populations. Each agent selects one strategy at a time and revises it repeatedly…

Systems and Control · Electrical Eng. & Systems 2020-10-21 Murat Arcak , Nuno C. Martins

We study the problem of computing an $\epsilon$-Nash equilibrium in repeated games. Earlier work by Borgs et al. [2010] suggests that this problem is intractable. We show that if we make a slight change to their model---modeling the players…

Computer Science and Game Theory · Computer Science 2015-03-24 Joseph Y. Halpern , Rafael Pass , Lior Seeman

Time-series forecasting is a critical challenge in various domains and has witnessed substantial progress in recent years. Many real-life scenarios, such as public health, economics, and social applications, involve feedback loops where…

Machine Learning · Computer Science 2025-06-04 Zhiyuan Zhao , Haoxin Liu , Alexander Rodriguez , B. Aditya Prakash

We show that the problem of finding an \epsilon-approximate Nash equilibrium of an n by n two-person games can be reduced to the computation of an (\epsilon/n)^2-approximate market equilibrium of a Leontief economy. Together with a recent…

Computer Science and Game Theory · Computer Science 2007-05-23 Li-Sha Huang , Shang-Hua Teng

In population games, a large population of players, modeled as a continuum, is divided into subpopulations, and the fitness or payoff of each subpopulation depends on the overall population composition. Evolutionary dynamics describe how…

Optimization and Control · Mathematics 2016-09-19 M. A. Mabrok , Jeff Shamma

Building upon the results in [Hinterm\"uller et al., SIAM J. Optim, '15], generalized Nash equilibrium problems are considered, in which the feasible set of each player is influenced by the decisions of their competitors. This is realized…

Optimization and Control · Mathematics 2021-10-22 Steven-Marian Stengl

This paper considers a class of generalized convex games where each player is associated with a convex objective function, a convex inequality constraint and a convex constraint set. The players aim to compute a Nash equilibrium through…

Optimization and Control · Mathematics 2015-09-23 Minghui Zhu , Emilio Frazzoli

We analyze Nesterov's accelerated gradient descent (NAGD) for Nash equilibrium seeking in $N$-player quadratic games. While the continuous-time NAGD dynamics -- the Su--Boyd--Cand\`{e}s ODE -- are well understood for convex optimization,…

Optimization and Control · Mathematics 2026-03-27 Jay Paek

The $\varepsilon$-well-supported Nash equilibrium is a strong notion of approximation of a Nash equilibrium, where no player has an incentive greater than $\varepsilon$ to deviate from any of the pure strategies that she uses in her mixed…

Computer Science and Game Theory · Computer Science 2014-07-14 Artur Czumaj , Michail Fasoulakis , Marcin Jurdziński

Several notions of game enjoy a Nash-like notion of equilibrium without guarantee of existence. There are different ways of weakening a definition of Nash-like equilibrium in order to guarantee the existence of a weakened equilibrium.…

Computer Science and Game Theory · Computer Science 2007-12-11 Stéphane Le Roux

The goal in this paper is to approximate the Price of Stability (PoS) in stochastic Nash games using stochastic approximation (SA) schemes. PoS is amongst the most popular metrics in game theory and provides an avenue for estimating the…

Optimization and Control · Mathematics 2023-10-31 Afrooz Jalilzadeh , Farzad Yousefian , Mohammadjavad Ebrahimi

Efficient computability is an important property of solution concepts in matching markets. We consider the computational complexity of finding and verifying various solution concepts in trading networks-multi-sided matching markets with…

Computational Complexity · Computer Science 2025-10-03 Tamás Fleiner , Zsuzsanna Jankó , Ildikó Schlotter , Alexander Teytelboym

We revisit the problem of physics-informed regression, and propose a method that directly computes the state at the prediction point, simultaneously with the derivative and curvature information of the existing samples. We frame each…

Optimization and Control · Mathematics 2025-12-16 Lorenzo Sabug , Eric Kerrigan

We study the complexity of equilibrium computation in discrete preference games. These games were introduced by Chierichetti, Kleinberg, and Oren (EC '13, JCSS '18) to model decision-making by agents in a social network that choose a…

Computer Science and Game Theory · Computer Science 2019-05-29 Phani Raj Lolakapuri , Umang Bhaskar , Ramasuri Narayanam , Gyana R Parija , Pankaj S Dayama

We consider the non-convex non-concave objective function in two-player zero-sum continuous games. The existence of pure Nash equilibrium requires stringent conditions, posing a major challenge for this problem. To circumvent this…

Optimization and Control · Mathematics 2024-11-20 Shihong Ding , Hanze Dong , Cong Fang , Zhouchen Lin , Tong Zhang

Precise description of population game dynamics introduced by revision protocols - an economic model describing the agent's propensity to switch to a better-performing strategy - is of importance in economics and social sciences in general.…

Dynamical Systems · Mathematics 2025-04-22 Jakub Bielawski , Łukasz Cholewa , Fryderyk Falniowski

We initiate the study of Preference-Based Multi-Agent Reinforcement Learning (PbMARL), exploring both theoretical foundations and empirical validations. We define the task as identifying the Nash equilibrium from a preference-only offline…

Machine Learning · Computer Science 2025-01-10 Natalia Zhang , Xinqi Wang , Qiwen Cui , Runlong Zhou , Sham M. Kakade , Simon S. Du

We present a unifying representation of computation as a two-player game between an \emph{Algorithm} and \emph{Nature}, grounded in domain theory and game theory. The Algorithm produces progressively refined approximations within a Scott…

Computational Complexity · Computer Science 2025-11-04 Paul Alexander Bilokon
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