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The Colonel Blotto game, formulated by Emile Borel, involves players allocating limited resources to multiple battlefields simultaneously, with the winner being the one who allocates more resources to each battlefield. Computation of the…

Computer Science and Game Theory · Computer Science 2025-07-31 Debtoru Chatterjee , Girish Tiwari , Niladri Chatterjee

Extensive-form games (EFGs) are a common model of multi-agent interactions with imperfect information. State-of-the-art algorithms for solving these games typically perform full walks of the game tree that can prove prohibitively slow in…

Computer Science and Game Theory · Computer Science 2019-07-24 Trevor Davis , Martin Schmid , Michael Bowling

This paper investigates a population-based training regime based on game-theoretic principles called Policy-Spaced Response Oracles (PSRO). PSRO is general in the sense that it (1) encompasses well-known algorithms such as fictitious play…

Games with incomplete preferences are an important model for studying rational decision-making in scenarios where players face incomplete information about their preferences and must contend with incomparable outcomes. We study the problem…

Computer Science and Game Theory · Computer Science 2024-08-13 Abhishek N. Kulkarni , Jie Fu , Ufuk Topcu

In this paper we consider the problem of finding a Nash equilibrium (NE) via zeroth-order feedback information in games with merely monotone pseudogradient mapping. Based on hybrid system theory, we propose a novel extremum seeking…

Systems and Control · Electrical Eng. & Systems 2021-09-17 Suad Krilašević , Sergio Grammatico

Optimizing strategic decisions (a.k.a. computing equilibrium) is key to the success of many non-cooperative multi-agent applications. However, in many real-world situations, we may face the exact opposite of this game-theoretic problem --…

Computer Science and Game Theory · Computer Science 2022-10-05 Jibang Wu , Weiran Shen , Fei Fang , Haifeng Xu

XOR games are the simplest model in which the nonlocal properties of entanglement manifest themselves. When there are two players, it is well known that the bias --- the maximum advantage over random play --- of entangled players can be at…

Quantum Physics · Physics 2015-05-30 Jop Briet , Thomas Vidick

This paper studies the last-iterate convergence properties of the exponential weights algorithm with constant learning rates. We consider a repeated interaction in discrete time, where each player uses an exponential weights algorithm…

Artificial Intelligence · Computer Science 2024-07-10 Maurizio d'Andrea , Fabien Gensbittel , Jérôme Renault

We study two-player security games which can be viewed as sequences of nonzero-sum matrix games played by an Attacker and a Defender. The evolution of the game is based on a stochastic fictitious play process. Players do not have access to…

Computer Science and Game Theory · Computer Science 2010-03-16 Kien C. Nguyen , Tansu Alpcan , Tamer Basar

While recent reductions of zero-sum partially observable stochastic games (zs-POSGs) to transition-independent stochastic games (TI-SGs) theoretically admit dynamic programming, practical solutions remain stifled by the inherent…

Computer Science and Game Theory · Computer Science 2026-05-04 Erwan C. Escudie , Matthia Sabatelli , Jilles S. Dibangoye

The standard game-theoretic solution concept, Nash equilibrium, assumes that all players behave rationally. If we follow a Nash equilibrium and opponents are irrational (or follow strategies from a different Nash equilibrium), then we may…

Computer Science and Game Theory · Computer Science 2023-08-22 Sam Ganzfried

The game-theoretic risk management framework put forth in the precursor work "Towards a Theory of Games with Payoffs that are Probability-Distributions" (arXiv:1506.07368 [q-fin.EC]) is herein extended by algorithmic details on how to…

General Economics · Economics 2020-04-10 Stefan Rass

We study the convergence of Optimistic Gradient Descent Ascent in unconstrained bilinear games. In a first part, we consider the zero-sum case and extend previous results by Daskalakis et al. in 2018, Liang and Stokes in 2019, and others:…

Optimization and Control · Mathematics 2022-11-24 Étienne de Montbrun , Jérôme Renault

Adversarial training, a special case of multi-objective optimization, is an increasingly prevalent machine learning technique: some of its most notable applications include GAN-based generative modeling and self-play techniques in…

Machine Learning · Statistics 2021-03-17 Gauthier Gidel , David Balduzzi , Wojciech Marian Czarnecki , Marta Garnelo , Yoram Bachrach

Quantitative games are two-player zero-sum games played on directed weighted graphs. Total-payoff games (that can be seen as a refinement of the well-studied mean-payoff games) are the variant where the payoff of a play is computed as the…

Computer Science and Game Theory · Computer Science 2015-07-15 Thomas Brihaye , Gilles Geeraerts , Axel Haddad , Benjamin Monmege

We provide an in-depth study of Nash equilibria in multi-objective normal form games (MONFGs), i.e., normal form games with vectorial payoffs. Taking a utility-based approach, we assume that each player's utility can be modelled with a…

Computer Science and Game Theory · Computer Science 2022-07-19 Willem Röpke , Diederik M. Roijers , Ann Nowé , Roxana Rădulescu

We study the computational complexity of solving stochastic games with mean-payoff objectives. Instead of identifying special classes in which simple strategies are sufficient to play $\epsilon$-optimally, or form $\epsilon$-Nash…

Computer Science and Game Theory · Computer Science 2024-05-16 Sougata Bose , Rasmus Ibsen-Jensen , Patrick Totzke

Function approximation (FA) has been a critical component in solving large zero-sum games. Yet, little attention has been given towards FA in solving \textit{general-sum} extensive-form games, despite them being widely regarded as being…

Computer Science and Game Theory · Computer Science 2023-04-04 Chun Kai Ling , J. Zico Kolter , Fei Fang

When can cooperation arise from self-interested decisions in public goods games? And how can we help agents to act cooperatively? We examine these classical questions in a pivotal participation game, a variant of public good games, where…

Computer Science and Game Theory · Computer Science 2021-08-27 Yiling Chen , Biaoshuai Tao , Fang-Yi Yu

The efficiency of a game is typically quantified by the price of anarchy (PoA), defined as the worst ratio of the objective function value of an equilibrium --- solution of the game --- and that of an optimal outcome. Given the tremendous…

Computer Science and Game Theory · Computer Science 2017-08-23 Nguyen Kim Thang