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We study a two-player Stackelberg game with incomplete information such that the follower's strategy belongs to a known family of parameterized functions with an unknown parameter vector. We design an adaptive learning approach to…

Computer Science and Game Theory · Computer Science 2021-01-12 Guosong Yang , Radha Poovendran , João P. Hespanha

We provide a novel approach to achieving a desired outcome in a coordination game: the original 2x2 game is embedded in a 2x3 game where one of the players may use a third action. For a large set of payoff values only one of the Nash…

Computer Science and Game Theory · Computer Science 2024-01-22 Sofia B. S. D. Castro

Many decentralized and networked control problems involve decision makers which have either misaligned criteria or subjective priors. In the context of such a setup, in this paper we consider binary signaling problems in which the decision…

Optimization and Control · Mathematics 2019-09-06 Serkan Sarıtaş , Sinan Gezici , Serdar Yüksel

Many communication, sensor network, and networked control problems involve agents (decision makers) which have either misaligned objective functions or subjective probabilistic models. In the context of such setups, we consider binary…

Optimization and Control · Mathematics 2019-09-09 Serkan Sarıtaş , Sinan Gezici , Serdar Yüksel

This paper proposes and studies a class of discrete-time finite-time-horizon Stackelberg mean-field games, with one leader and an infinite number of identical and indistinguishable followers. In this game, the objective of the leader is to…

Optimization and Control · Mathematics 2022-10-11 Xin Guo , Anran Hu , Jiacheng Zhang

In two-player zero-sum stochastic games, where two competing players make decisions under uncertainty, a pair of optimal strategies is traditionally described by Nash equilibrium and computed under the assumption that the players have…

Optimization and Control · Mathematics 2019-07-30 Yagiz Savas , Mohamadreza Ahmadi , Takashi Tanaka , Ufuk Topcu

We analyze a two-player, nonzero-sum Dynkin game of stopping with incomplete information. We assume that each player observes his own Brownian motion, which is not only independent of the other player's Brownian motion but also not…

Probability · Mathematics 2025-04-16 Georgy Gaitsgori , Richard Groenewald

This paper investigates the convergence of learning dynamics in Stackelberg games. In the class of games we consider, there is a hierarchical game being played between a leader and a follower with continuous action spaces. We establish a…

Computer Science and Game Theory · Computer Science 2024-12-07 Tanner Fiez , Benjamin Chasnov , Lillian J. Ratliff

We study the sample complexity of identifying an approximate equilibrium for two-player zero-sum $n\times 2$ matrix games. That is, in a sequence of repeated game plays, how many rounds must the two players play before reaching an…

Computer Science and Game Theory · Computer Science 2023-03-21 Arnab Maiti , Kevin Jamieson , Lillian J. Ratliff

A Dynkin game is a zero-sum, stochastic stopping game between two players where either player can stop the game at any time for an observable payoff. Typically the payoff process of the max-player is assumed to be smaller than the payoff…

Probability · Mathematics 2020-08-18 Ivan Guo

We consider zero-sum stochastic games with perfect information and finitely many states and actions. The payoff is computed by a function which associates to each infinite sequence of states and actions a real number. We prove that if the…

Computer Science and Game Theory · Computer Science 2022-03-29 Hugo Gimbert , Edon Kelmendi

In this paper we study continuous-time two-player zero-sum optimal switching games on a finite horizon. Using the theory of doubly reflected BSDEs with interconnected barriers, we show that this game has a value and an equilibrium in the…

Optimization and Control · Mathematics 2018-06-04 Said Hamadène , Randall Martyr , John Moriarty

In this paper we consider two-person zero-sum risk-sensitive stochastic dynamic games with Borel state and action spaces and bounded reward. The term risk-sensitive refers to the fact that instead of the usual risk neutral optimization…

Optimization and Control · Mathematics 2021-07-21 Nicole Bäuerle , Ulrich Rieder

In this paper we introduce and study {\em all-pay bidding games}, a class of two player, zero-sum games on graphs. The game proceeds as follows. We place a token on some vertex in the graph and assign budgets to the two players. Each turn,…

Computer Science and Game Theory · Computer Science 2019-11-20 Guy Avni , Rasmus Ibsen-Jensen , Josef Tkadlec

Existing methods for learning Stackelberg equilibria typically assume that the followers' (variational, generalized) Nash equilibrium is unique. However, in the presence of multiple equilibria, without a selection convention, the problem…

Optimization and Control · Mathematics 2026-04-30 Silvia Cianchi , Anibal Sanjab , Sergio Grammatico

The design of Nash equilibrium seeking strategies for games in which the involved players are of second-order integrator-type dynamics is investigated in this paper. Noticing that velocity signals are usually noisy or not available for…

Optimization and Control · Mathematics 2020-06-18 Maojiao Ye , Jizhao Yin , Le Yin

This article introduces a class of $Nash$ games among $Stackelberg$ players ($NASPs$), namely, a class of simultaneous non-cooperative games where the players solve sequential Stackelberg games. Specifically, each player solves a…

Computer Science and Game Theory · Computer Science 2025-03-04 Margarida Carvalho , Gabriele Dragotto , Felipe Feijoo , Andrea Lodi , Sriram Sankaranarayanan

In this paper, we consider two-player zero-sum matrix and stochastic games and develop learning dynamics that are payoff-based, convergent, rational, and symmetric between the two players. Specifically, the learning dynamics for matrix…

Machine Learning · Computer Science 2024-09-06 Zaiwei Chen , Kaiqing Zhang , Eric Mazumdar , Asuman Ozdaglar , Adam Wierman

We study a class of two-player zero-sum stochastic games known as \textit{blind stochastic games}, where players neither observe the state nor receive any information about it during the game. A central concept for analyzing long-duration…

Optimization and Control · Mathematics 2025-11-24 Krishnendu Chatterjee , David Lurie , Raimundo Saona , Bruno Ziliotto

A recent body of experimental literature has studied empirical game-theoretical analysis, in which we have partial knowledge of a game, consisting of observations of a subset of the pure-strategy profiles and their associated payoffs to…

Computer Science and Game Theory · Computer Science 2014-02-13 John Fearnley , Martin Gairing , Paul Goldberg , Rahul Savani