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It is known that there are uncoupled learning heuristics leading to Nash equilibrium in all finite games. Why should players use such learning heuristics and where could they come from? We show that there is no uncoupled learning heuristic…

Computer Science and Game Theory · Computer Science 2015-04-27 Burkhard C. Schipper

We analyse the computational complexity of finding Nash equilibria in turn-based stochastic multiplayer games with omega-regular objectives. We show that restricting the search space to equilibria whose payoffs fall into a certain interval…

Computer Science and Game Theory · Computer Science 2015-07-01 Michael Ummels , Dominik Wojtczak

Contrary to the customary view that the celebrated Nash-equilibrium theorem in Game Theory is paradigmatic for non-cooperative games, it is shown that, in fact, it is essentially based on a particularly strong cooperation assumption.…

Optimization and Control · Mathematics 2007-05-23 Elemer E Rosinger

A robust game is a distribution-free model to handle ambiguity generated by a bounded set of possible realizations of the values of players' payoff functions. The players are worst-case optimizers and a solution, called robust-optimization…

Theoretical Economics · Economics 2020-02-11 Giovanni Paolo Crespi , Davide Radi , Matteo Rocca

In this study, we investigate $N$-player stochastic differential games with regime switching, where the player dynamics are modulated by a finite-state Markov chain. We analyze the associated Nash system, which consists of a system of…

Probability · Mathematics 2025-02-26 Mingrui Wang , Prakash Chakraborty

We introduce a simple stochastic dynamics for game theory. It assumes ``local'' rationality in the sense that any player climbs the gradient of his utility function in the presence of a stochastic force which represents deviation from…

Statistical Mechanics · Physics 2008-11-23 Matteo Marsili , Yi-Cheng Zhang

We study stochastic mean-field games among finite number of teams with large finite as well as infinite number of decision makers. For this class of games within static and dynamic settings, we establish the existence of a Nash equilibrium,…

Optimization and Control · Mathematics 2022-11-11 Sina Sanjari , Naci Saldi , Serdar Yüksel

We consider a large population dynamic game in discrete time where players are characterized by time-evolving types. It is a natural assumption that the players' actions cannot anticipate future values of their types. Such games go under…

Optimization and Control · Mathematics 2022-03-01 Julio Backhoff-Veraguas , Xin Zhang

In this paper, I prove that existence of pure-strategy Nash equilibrium in games with infinitely many players is equivalent to the axiom of choice.

Logic · Mathematics 2023-06-06 Conrad Kosowsky

Nash equilibrium serves as a fundamental mathematical tool in economics and game theory. However, it classically assumes knowledge of player utilities, whereas economics generally regards preferences as more fundamental. To leverage…

Computer Science and Game Theory · Computer Science 2026-05-11 Ian Gemp , Crystal Qian , Marc Lanctot , Kate Larson

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

Secure equilibrium is a refinement of Nash equilibrium, which provides some security to the players against deviations when a player changes his strategy to another best response strategy. The concept of secure equilibrium is specifically…

Computer Science and Game Theory · Computer Science 2014-05-08 Julie De Pril , János Flesch , Jeroen Kuipers , Gijs Schoenmakers , Koos Vrieze

In this paper we investigate Nash equilibrium payoffs for two-player nonzero-sum stochastic differential games whose cost functionals are defined by a system of coupled backward stochastic differential equations. We obtain an existence…

Probability · Mathematics 2014-01-21 Qian Lin

Multi-agent reinforcement learning is a challenging and active field of research due to the inherent nonstationary property and coupling between agents. A popular approach to modeling the multi-agent interactions underlying the multi-agent…

Multiagent Systems · Computer Science 2025-10-07 Jushan Chen , Santiago Paternain

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…

Computer Science and Game Theory · Computer Science 2021-09-20 Tobias Winkler , Maximilian Weininger

We consider a non-cooperative constrained stochastic games with N players with the following special structure. With each player there is an associated controlled Markov chain. The transition probabilities of the i-th Markov chain depend…

Information Theory · Computer Science 2007-07-13 E. Altman , K. Avrachenkov , N. Bonneau , M. Debbah , R. El-Azouzi , D. Sadoc Menasche

A significant roadblock to the development of principled multi-agent reinforcement learning is the fact that desired solution concepts like Nash equilibria may be intractable to compute. To overcome this obstacle, we take inspiration from…

Computer Science and Game Theory · Computer Science 2024-08-28 Eric Mazumdar , Kishan Panaganti , Laixi Shi

We are interested in the study of stochastic games for which each player faces an optimal stopping problem. In our setting, the players may interact through the criterion to optimise as well as through their dynamics. After briefly…

Probability · Mathematics 2025-09-03 Dylan Possamaï , Mehdi Talbi

We construct a finite deterministic graphical (DG) game without Nash equilibria in pure stationary strategies. This game has 3 players $I=\{1,2,3\}$ and 5 outcomes: 2 terminal $a_1$ and $a_2$ and 3 cyclic. Furthermore, for 2 players a…

Combinatorics · Mathematics 2024-12-24 Bogdan Butyrin , Vladimir Gurvich , Anton Lutsenko , Mariya Naumova , Maxim Peskin

Game theory studies situations in which strategic players can modify the state of a given system, due to the absence of a central authority. Solution concepts, such as Nash equilibrium, are defined to predict the outcome of such situations.…

Computer Science and Game Theory · Computer Science 2013-11-08 Diodato Ferraioli , Paul W. Goldberg , Carmine Ventre
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