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We introduce a new non-zero-sum game of optimal stopping with asymmetric exercise opportunities. Given a stochastic process modelling the value of an asset, one player observes and can act on the process continuously, while the other player…

Probability · Mathematics 2024-05-16 José Luis Pérez , Neofytos Rodosthenous , Kazutoshi Yamazaki

We propose a novel method to find Nash equilibria in games with binary decision variables by including compensation payments and incentive-compatibility constraints from non-cooperative game theory directly into an optimization framework in…

Optimization and Control · Mathematics 2017-10-10 Daniel Huppmann , Sauleh Siddiqui

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

In nature and society problems arise when different interests are difficult to reconcile, which are modeled in game theory. While most applications assume uncorrelated games, a more detailed modeling is necessary to consider the…

Physics and Society · Physics 2019-08-21 A. D. Correia , H. T. C. Stoof

This work considers two-player zero-sum semi-Markov games with incomplete information on one side and perfect observation. At the beginning, the system selects a game type according to a given probability distribution and informs to Player…

Optimization and Control · Mathematics 2021-07-16 Fang Chen , Xianping Guo , Zhong-Wei Liao

In this paper, the open-loop and closed-loop local and remote stochastic nonzero-sum game (LRSNG) problem is investigated. Different from previous works, the stochastic nonzero-sum game problem under consideration is essentially a special…

Optimization and Control · Mathematics 2022-12-20 Xin Li , Qingyuan Qi , Xinbei Lv

Contemporary applications of machine learning in two-team e-sports and the superior expressivity of multi-agent generative adversarial networks raise important and overlooked theoretical questions regarding optimization in two-team games.…

Computer Science and Game Theory · Computer Science 2023-04-18 Fivos Kalogiannis , Ioannis Panageas , Emmanouil-Vasileios Vlatakis-Gkaragkounis

We study equilibrium concepts in non-cooperative games under uncertainty where both beliefs and mixed strategies are represented by non-additive measures (capacities). In contrast to the classical Nash framework based on additive…

Computer Science and Game Theory · Computer Science 2026-03-06 Taras Radul

We formulate two-party policy competition as a two-player non-cooperative game, generalizing Lin et al.'s work (2021). Each party selects a real-valued policy vector as its strategy from a compact subset of Euclidean space, and a voter's…

Computer Science and Game Theory · Computer Science 2026-03-19 Chuang-Chieh Lin , Chi-Jen Lu , Po-An Chen , Chih-Chieh Hung

Unlike Poker where the action space $\mathcal{A}$ is discrete, differential games in the physical world often have continuous action spaces not amenable to discrete abstraction, rendering no-regret algorithms with…

Computer Science and Game Theory · Computer Science 2025-02-17 Mukesh Ghimire , Zhe Xu , Yi Ren

This paper investigates the equilibrium convergence properties of a proposed algorithm for potential games with continuous strategy spaces in the presence of feedback delays, a main challenge in multi-agent systems that compromises the…

Optimization and Control · Mathematics 2023-03-20 Yuanhanqing Huang , Jianghai Hu

This paper is concerned with a linear-quadratic non-zero sum differential game with asymmetric delayed information. To be specific, two players exist time delays simultaneously which are different, leading the dynamical system being an…

Optimization and Control · Mathematics 2025-10-27 Yuxin Ye , Jingtao Shi

The Team-maxmin equilibrium prescribes the optimal strategies for a team of rational players sharing the same goal and without the capability of correlating their strategies in strategic games against an adversary. This solution concept can…

Artificial Intelligence · Computer Science 2016-11-21 Nicola Basilico , Andrea Celli , Giuseppe De Nittis , Nicola Gatti

We study the open question of how players learn to play a social optimum pure-strategy Nash equilibrium (PSNE) through repeated interactions in general-sum coordination games. A social optimum of a game is the stable Pareto-optimal state…

Computer Science and Game Theory · Computer Science 2023-07-26 Duong Nguyen , Langford White , Hung Nguyen

Many real-world domains contain multiple agents behaving strategically with probabilistic transitions and uncertain (potentially infinite) duration. Such settings can be modeled as stochastic games. While algorithms have been developed for…

Computer Science and Game Theory · Computer Science 2020-06-25 Sam Ganzfried , Conner Laughlin , Charles Morefield

The large majority of risk-sharing transactions involve few agents, each of whom can heavily influence the structure and the prices of securities. This paper proposes a game where agents' strategic sets consist of all possible sharing…

Risk Management · Quantitative Finance 2016-07-11 Michail Anthropelos , Constantinos Kardaras

We consider the problem of computing mixed Nash equilibria of two-player zero-sum games with continuous sets of pure strategies and with first-order access to the payoff function. This problem arises for example in game-theory-inspired…

Optimization and Control · Mathematics 2025-09-04 Guillaume Wang , Lénaïc Chizat

We study $n$-dimensional contests between two players with heterogeneous effort costs, where each dimension (battle) is modeled as a Tullock contest. Prize-allocation rules are identity-independent, budget-balanced, and weakly increasing in…

Theoretical Economics · Economics 2026-03-31 Siyuan Fan , Zhonghong Kuang , Jingfeng Lu

We propose a general class of symmetric games called position-optimization games. Given a probability distribution $Q$ over a set of targets $\mathcal{Y}$, the $n$ players each choose a position in a space $\mathcal{X}$. A player's utility…

Computer Science and Game Theory · Computer Science 2026-02-18 Rafael Frongillo , Melody Hsu , Mary Monroe , Anish Thilagar

We propose a toy model for a stochastic description of the competition between two athletes of unequal strength, whose average strength difference is represented by a parameter $d$. The athletes interact through the choice of their…

Physics and Society · Physics 2019-05-24 Cecile Appert-Rolland , Hendrik-Jan Hilhorst , Amandine Aftalion
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