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This paper examines multiplayer symmetric constant-sum games with more than two players in a competitive setting, including examples like Mahjong, Poker, and various board and video games. In contrast to two-player zero-sum games,…

Machine Learning · Computer Science 2024-10-04 Jiawei Ge , Yuanhao Wang , Wenzhe Li , Chi Jin

We revisit Blackwell's celebrated approachability problem which considers a repeated vector-valued game between a player and an adversary. Motivated by settings in which the action set of the player or adversary (or both) is difficult to…

Optimization and Control · Mathematics 2025-06-17 Dan Garber , Mhna Massalha

We study minimum entropy submodular optimization, a common generalization of the minimum entropy set cover problem, studied earlier by Cardinal et al., and the submodular set cover problem. We give a general bound of the approximation…

Data Structures and Algorithms · Computer Science 2014-02-19 Cosmin Bonchiş , Gabriel Istrate

We define and study a lending game to model the interbank money market, in which lending banks strategically allocate their cash to borrowing banks. The interest rate offered by each borrowing bank is within the interest rate corridor set…

Computer Science and Game Theory · Computer Science 2026-02-18 Jinyun Tong , Bart de Keijzer , Haoxiang Wang , Carmine Ventre

Zero-sum stochastic games generalize the notion of Markov Decision Processes (i.e. controlled Markov chains, or stochastic dynamic programming) to the 2-player competitive case : two players jointly control the evolution of a state…

Optimization and Control · Mathematics 2019-05-17 Jérôme Renault

We consider a finite number of $N$ statistically equal agents, each moving on a finite set of states according to a continuous-time Markov Decision Process (MDP). Transition intensities of the agents and generated rewards depend not only on…

Probability · Mathematics 2025-09-23 Nicole Bäuerle , Sebastian Höfer

Recently there is a large amount of work devoted to the study of Markov chain stochastic gradient methods (MC-SGMs) which mainly focus on their convergence analysis for solving minimization problems. In this paper, we provide a…

Machine Learning · Statistics 2022-09-19 Puyu Wang , Yunwen Lei , Yiming Ying , Ding-Xuan Zhou

Recent work has led to the development of an elegant theory of Linearly Solvable Markov Decision Processes (LMDPs) and related Path-Integral Control Problems. Traditionally, MDPs have been formulated using stochastic policies and a control…

Systems and Control · Computer Science 2012-02-20 Krishnamurthy Dvijotham , Emanuel Todorov

We study the game modification problem, where a benevolent game designer or a malevolent adversary modifies the reward function of a zero-sum Markov game so that a target deterministic or stochastic policy profile becomes the unique Markov…

Computer Science and Game Theory · Computer Science 2024-08-27 Young Wu , Jeremy McMahan , Yiding Chen , Yudong Chen , Xiaojin Zhu , Qiaomin Xie

We consider zero-sum stochastic games with finite state and action spaces, perfect information, mean payoff criteria, without any irreducibility assumption on the Markov chains associated to strategies (multichain games). The value of such…

Optimization and Control · Mathematics 2012-08-03 Marianne Akian , Jean Cochet-Terrasson , Sylvie Detournay , Stéphane Gaubert

The bounded mean betting procedure serves as a crucial interface between the domains of (1) sequential, anytime-valid statistical inference, and (2) online learning and portfolio selection algorithms. While recent work in both domains has…

Probability · Mathematics 2026-05-05 Hongjian Wang , Shubhada Agrawal , Aaditya Ramdas

We study security threats to Markov games due to information asymmetry and misinformation. We consider an attacker player who can spread misinformation about its reward function to influence the robust victim player's behavior. Given a…

Machine Learning · Computer Science 2024-06-26 Jeremy McMahan , Young Wu , Yudong Chen , Xiaojin Zhu , Qiaomin Xie

We address the question of whether price of stability results (existence of equilibria with low social cost) are robust to incomplete information. We show that this is the case in potential games, if the underlying algorithmic social cost…

Computer Science and Game Theory · Computer Science 2015-03-13 Vasilis Syrgkanis

Min-max optimization problems (i.e., min-max games) have been attracting a great deal of attention because of their applicability to a wide range of machine learning problems. Although significant progress has been made recently, the…

Computer Science and Game Theory · Computer Science 2023-07-07 Denizalp Goktas , Amy Greenwald

The key assumption underlying linear Markov Decision Processes (MDPs) is that the learner has access to a known feature map $\phi(x, a)$ that maps state-action pairs to $d$-dimensional vectors, and that the rewards and transitions are…

Machine Learning · Computer Science 2023-09-20 Noah Golowich , Ankur Moitra , Dhruv Rohatgi

Policy-based methods with function approximation are widely used for solving two-player zero-sum games with large state and/or action spaces. However, it remains elusive how to obtain optimization and statistical guarantees for such…

Machine Learning · Computer Science 2022-03-01 Yulai Zhao , Yuandong Tian , Jason D. Lee , Simon S. Du

Classical objectives in two-player zero-sum games played on graphs often deal with limit behaviors of infinite plays: e.g., mean-payoff and total-payoff in the quantitative setting, or parity in the qualitative one (a canonical way to…

Logic in Computer Science · Computer Science 2016-09-21 Véronique Bruyère , Quentin Hautem , Mickael Randour

Wealthy individuals may be less tempted to defect than those with comparatively low payoffs. To take this into consideration, we introduce coevolutionary success-driven multigames in structured populations. While the core game is always the…

Physics and Society · Physics 2014-10-17 Attila Szolnoki , Matjaz Perc

An instance $I$ of the Stable Matching Problem (SMP) is given by a bipartite graph with a preference list of neighbors for every vertex. A swap in $I$ is the exchange of two consecutive vertices in a preference list. A swap can be viewed as…

Data Structures and Algorithms · Computer Science 2022-11-16 Eduard Eiben , Gregory Gutin , Philip R. Neary , Clément Rambaud , Magnus Wahlström , Anders Yeo

In a financial market model, we consider variations of the problem of minimizing the expected time to upcross a certain wealth level. For exponential Levy markets, we show the asymptotic optimality of the growth-optimal portfolio for the…

Portfolio Management · Quantitative Finance 2009-04-14 Constantinos Kardaras , Eckhard Platen
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