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The distributed computation of equilibria and optima has seen growing interest in a broad collection of networked problems. We consider the computation of equilibria of convex stochastic Nash games characterized by a possibly nonconvex…

Optimization and Control · Mathematics 2019-08-05 Jinlong Lei , Uday V. Shanbhag

This paper studies a class of network games with linear-quadratic payoffs and externalities exerted through a strictly concave interaction function. This class of game is motivated by the diminishing marginal effects with peer influences.…

Optimization and Control · Mathematics 2024-06-04 Jiamin Cai , Chenyue Zhang , Hoi-To Wai

In 1975 the first author proved that every finite tight two-person game form $g$ is Nash-solvable, that is, for every payoffs $u$ and $w$ of two players the obtained game $(g;u,w)$, in normal form, has a Nash equilibrium (NE) in pure…

Computer Science and Game Theory · Computer Science 2023-06-21 Vladimir Gurvich , Mariya Naumova

Automated verification techniques for stochastic games allow formal reasoning about systems that feature competitive or collaborative behaviour among rational agents in uncertain or probabilistic settings. Existing tools and techniques…

Logic in Computer Science · Computer Science 2020-09-01 Marta Kwiatkowska , Gethin Norman , David Parker , Gabriel Santos

Stochastic games combine controllable and adversarial non-determinism with stochastic behavior and are a common tool in control, verification and synthesis of reactive systems facing uncertainty. Multi-objective stochastic games are natural…

Computational Complexity · Computer Science 2022-07-21 Tobias Winkler , Maximilian Weininger

The game-theoretic risk management framework put forth in the precursor work "Towards a Theory of Games with Payoffs that are Probability-Distributions" (arXiv:1506.07368 [q-fin.EC]) is herein extended by algorithmic details on how to…

General Economics · Economics 2020-04-10 Stefan Rass

This work studies an independent natural policy gradient (NPG) algorithm for the multi-agent reinforcement learning problem in Markov potential games. It is shown that, under mild technical assumptions and the introduction of the…

Machine Learning · Computer Science 2023-10-30 Youbang Sun , Tao Liu , Ruida Zhou , P. R. Kumar , Shahin Shahrampour

In this paper, we address the inverse problem in the case of linear-quadratic discrete-time dynamic non-cooperative games. Given feedback laws of players that are known to be a Nash equilibrium pair for a discrete-time linear system, we…

Optimization and Control · Mathematics 2024-07-19 Emin Martirosyan , Ming Cao

We formulate and study a class of two-player zero-sum stochastic dynamic games with partial and asymmetric information. Information asymmetry introduces fundamental challenges involving \emph{belief representation} and \emph{theory of mind}…

Optimization and Control · Mathematics 2026-03-20 Yuxiang Guan , Iman Shames , Tyler Summers

In this paper, we study network games where players are involved in information aggregation processes subject to the differential privacy requirement for players' payoff functions. We propose a Laplace linear-quadratic functional…

Computer Science and Game Theory · Computer Science 2023-03-21 Yijun Chen , Guodong Shi

In recent work, semantic games of independence-friendly logic were studied in strategic form in terms of (mixed strategy) Nash equilibria. The class of strategic games of independence-friendly logic is contained in the class of win-loss,…

Logic · Mathematics 2014-01-21 Merlijn Sevenster

Environments with multi-agent interactions often result a rich set of modalities of behavior between agents due to the inherent suboptimality of decision making processes when agents settle for satisfactory decisions. However, existing…

Optimization and Control · Mathematics 2022-02-03 Oswin So , Kyle Stachowicz , Evangelos A. Theodorou

This paper considers a class of mean field linear-quadratic-Gaussian (LQG) games with model uncertainty. The drift term in the dynamics of the agents contains a common unknown function. We take a robust optimization approach where a…

Optimization and Control · Mathematics 2017-01-03 Jianhui Huang , Minyi Huang

The goal of this paper is to study a multi-objective linear quadratic Gaussian (LQG) control problem. In particular, we consider an optimal control problem minimizing a quadratic cost over a finite time horizon for linear stochastic systems…

Optimization and Control · Mathematics 2021-06-01 Donghwan Lee , Do Wan Kim

We consider the problem of computing Nash equilibria in potential games where each player's strategy set is subject to private uncoupled constraints. This scenario is frequently encountered in real-world applications like road network…

Computer Science and Game Theory · Computer Science 2024-02-13 Nikolas Patris , Stelios Stavroulakis , Fivos Kalogiannis , Rose Zhang , Ioannis Panageas

Concurrent multi-player games with $\omega$-regular objectives are a standard model for systems that consist of several interacting components, each with its own objective. The standard solution concept for such games is Nash Equilibrium,…

Computer Science and Game Theory · Computer Science 2022-09-28 Shaull Almagor , Shai Guendelman

This paper is concerned with an overlapping information linear-quadratic (LQ) Stackelberg stochastic differential game with two leaders and two followers, where the diffusion terms of the state equation contain both the control and state…

Optimization and Control · Mathematics 2024-01-17 Yu Si , Jingtao Shi

This paper provides effective methods for the polyhedral formulation of impartial finite combinatorial games as lattice games. Given a rational strategy for a lattice game, a polynomial time algorithm is presented to decide (i) whether a…

Combinatorics · Mathematics 2011-05-30 Alan Guo , Ezra Miller

In an inverse game problem, one needs to infer the cost function of the players in a game such that a desired joint strategy is a Nash equilibrium. We study the inverse game problem for a class of multiplayer matrix games, where the cost…

Computer Science and Game Theory · Computer Science 2022-10-17 Yue Yu , Jonathan Salfity , David Fridovich-Keil , Ufuk Topcu

In this paper, we propose an initial value fomulation of the discrete mean field games on finite graphs (Graph MFG), and design a neural network based approach to solve it. Graph MFG describes infinite, non-cooperative and interactive…

Numerical Analysis · Mathematics 2026-04-08 Yaxin Feng , Yang Xiang , Haomin Zhou
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