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We study a class of zero-sum stochastic games between a stopper and a singular-controller, previously considered in [Bovo and De Angelis (2025)]. The underlying singularly-controlled dynamics takes values in…

Optimization and Control · Mathematics 2025-06-25 Andrea Bovo , Alessandro Milazzo

We study a class of deterministic mean field games and related optimal control problems, with a finite time horizon and in which the state space is a network. An agent controls her velocity, and, when she occupies a vertex, she can either…

Optimization and Control · Mathematics 2025-11-25 Yves Achdou , Claudio Marchi , Nicoletta Tchou

We construct a saddle point in a class of zero-sum games between a stopper and a singular-controller. The underlying dynamics is a one-dimensional, time-homogeneous, singularly controlled diffusion taking values either on $\mathbb{R}$ or on…

Optimization and Control · Mathematics 2024-10-28 Andrea Bovo , Tiziano De Angelis

It is well known that the rock-paper-scissors game has no pure saddle point. We show that this holds more generally: A symmetric two-player zero-sum game has a pure saddle point if and only if it is not a generalized rock-paper-scissors…

Computer Science and Game Theory · Computer Science 2013-01-25 Peter Duersch , Joerg Oechssler , Burkhard C. Schipper

This paper provides sufficient conditions for the existence of solutions for two-person zero-sum games with inf/sup-compact payoff functions and with possibly noncompact decision sets for both players. Payoff functions may be unbounded, and…

Optimization and Control · Mathematics 2021-12-22 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

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

Mertens [In Proceedings of the International Congress of Mathematicians (Berkeley, Calif., 1986) (1987) 1528-1577 Amer. Math. Soc.] proposed two general conjectures about repeated games: the first one is that, in any two-person zero-sum…

Optimization and Control · Mathematics 2016-03-16 Bruno Ziliotto

We study two-player zero-sum stochastic games, and propose a form of independent learning dynamics called Doubly Smoothed Best-Response dynamics, which integrates a discrete and doubly smoothed variant of the best-response dynamics into…

Computer Science and Game Theory · Computer Science 2023-03-07 Zaiwei Chen , Kaiqing Zhang , Eric Mazumdar , Asuman Ozdaglar , Adam Wierman

It was shown in Flesch and Solan (2022) with a rather involved proof that all two-player stochastic games with finite state and action spaces and shift-invariant payoffs admit an $\epsilon$-equilibrium, for every $\epsilon>0$. Their proof…

Optimization and Control · Mathematics 2022-08-25 Galit Ashkenazi-Golan , János Flesch , Eilon Solan

We study continuity properties of stochastic game problems with respect to various topologies on information structures, defined as probability measures characterizing a game. We will establish continuity properties of the value function…

Optimization and Control · Mathematics 2022-11-02 Ian Hogeboom-Burr , Serdar Yüksel

We study $\lambda$-discounted zero-sum games as the discount factor $\lambda$ approaches $0$ (that is, the players are more and more patient), in the context of games with stage duration. In stochastic games with stage duration $h$, players…

Optimization and Control · Mathematics 2026-02-20 Ivan Novikov

In this paper, we study the notion of adversarial Stackelberg value for two-player non-zero sum games played on bi-weighted graphs with the mean-payoff and the discounted sum functions. The adversarial Stackelberg value of Player 0 is the…

Computer Science and Game Theory · Computer Science 2020-05-05 Emmanuel Filiot , Raffaella Gentilini , Jean-François Raskin

We study two-player zero-sum repeated games with incomplete information on one side, where the payoff function is tail measurable (and not necessarily the long-run average payoff). We show that the maxmin value equals the concavification of…

Optimization and Control · Mathematics 2025-12-02 Gil Bar Castellon Koltun , Ehud Lehrer , Eilon Solan

We consider N-player and mean field games in continuous time over a finite horizon, where the position of each agent belongs to {-1,1}. If there is uniqueness of mean field game solutions, e.g. under monotonicity assumptions, then the…

Optimization and Control · Mathematics 2019-02-06 Alekos Cecchin , Paolo Dai Pra , Markus Fischer , Guglielmo Pelino

This paper considers a formulation of a differential game with constrained dynamics, where one player selects the dynamics and the other selects the applicable cost. When the game is considered on a finite time horizon, its value satisfies…

Optimization and Control · Mathematics 2009-09-25 Rami Atar , Paul Dupuis

We propose a sequential optimizing betting strategy in the multi-dimensional bounded forecasting game in the framework of game-theoretic probability of Shafer and Vovk (2001). By studying the asymptotic behavior of its capital process, we…

Probability · Mathematics 2011-02-16 Masayuki Kumon , Akimichi Takemura , Kei Takeuchi

We study the asymptotic behavior of the ratio of total return (or total profit) to total amount bet in a casino game. While the limit is well understood when the sequence of wagers is independent and identically distributed, here we…

Probability · Mathematics 2025-12-25 S. N. Ethier , L. Stefanello

In this paper we obtain Sobolev estimates for weak solutions of first oder variational Mean Field Game systems with coupling terms that are local function of the density variable. Under some coercivity condition on the coupling, we obtain…

Analysis of PDEs · Mathematics 2018-01-25 P. Jameson Graber , Alpár R. Mészáros

We consider Gillette's two-person zero-sum stochastic games with perfect information. For each $k \in \ZZ_+$ we introduce an effective reward function, called $k$-total. For $k = 0$ and $1$ this function is known as {\it mean payoff} and…

Discrete Mathematics · Computer Science 2015-08-17 Endre Boros , Khaled Elbassioni , Vladimir Gurvich , Kazuhisa Makino

We propose a learning dynamics to model how strategic agents repeatedly play a continuous game while relying on an information platform to learn an unknown payoff-relevant parameter. In each time step, the platform updates a belief estimate…

Multiagent Systems · Computer Science 2023-11-02 Manxi Wu , Saurabh Amin , Asuman Ozdaglar