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We study a class of distributionally robust games where agents are allowed to heterogeneously choose their risk aversion with respect to distributional shifts of the uncertainty. In our formulation, heterogeneous Wasserstein ball…

Optimization and Control · Mathematics 2025-12-08 Zifan Wang , Georgios Pantazis , Sergio Grammatico , Michael M. Zavlanos , Karl H. Johansson

Stochastic games generalize Markov decision processes (MDPs) to a multiagent setting by allowing the state transitions to depend jointly on all player actions, and having rewards determined by multiplayer matrix games at each state. We…

Computer Science and Game Theory · Computer Science 2013-01-18 Michael Kearns , Yishay Mansour , Satinder Singh

We introduce a simple stochastic dynamics for game theory. It assumes ``local'' rationality in the sense that any player climbs the gradient of his utility function in the presence of a stochastic force which represents deviation from…

Statistical Mechanics · Physics 2008-11-23 Matteo Marsili , Yi-Cheng Zhang

We investigate mean field games for players, who are weakly coupled via their empirical measure. To this end we investigate time-dependent pure jump type propagators over a finite space in the framework of non-linear Markov processes. We…

Optimization and Control · Mathematics 2015-03-25 Rani Basna , Astrid Hilbert , Vassili N. Kolokoltsov

This paper provides theoretical bounds for empirical game theoretical analysis of complex multi-agent interactions. We provide insights in the empirical meta game showing that a Nash equilibrium of the meta-game is an approximate Nash…

Computer Science and Game Theory · Computer Science 2018-03-20 Karl Tuyls , Julien Perolat , Marc Lanctot , Joel Z Leibo , Thore Graepel

This paper is concerned with a new class of mean-field games which involve a finite number of agents. Necessary and sufficient conditions are obtained for the existence of the decentralized open-loop Nash equilibrium in terms of…

Optimization and Control · Mathematics 2022-06-14 Bing-Chang Wang , Huanshui Zhang , Minyue Fu , Yong Liang

One of the main challenges in distributed learning arises from the difficulty of handling heterogeneous local models and data. In light of the recent success of generative models, we propose to meet this challenge by building on the idea of…

Machine Learning · Computer Science 2025-11-04 Dmitrij Schlesinger , Boris Flach

Nash equilibrium serves as a fundamental mathematical tool in economics and game theory. However, it classically assumes knowledge of player utilities, whereas economics generally regards preferences as more fundamental. To leverage…

Computer Science and Game Theory · Computer Science 2026-05-11 Ian Gemp , Crystal Qian , Marc Lanctot , Kate Larson

This paper examines the convergence behaviour of simultaneous best-response dynamics in random potential games. We provide a theoretical result showing that, for two-player games with sufficiently many actions, the dynamics converge quickly…

Computer Science and Game Theory · Computer Science 2025-05-19 Galit Ashkenazi-Golan , Domenico Mergoni Cecchelli , Edward Plumb

Game theory provides a general mathematical background to study the effect of pair interactions and evolutionary rules on the macroscopic behavior of multi-player games where players with a finite number of strategies may represent a wide…

Physics and Society · Physics 2016-04-20 Gyorgy Szabo , Istvan Borsos

We study a game-theoretic variant of the maximum circulation problem. In a flow allocation game, we are given a directed flow network. Each node is a rational agent and can strategically allocate any incoming flow to the outgoing edges.…

Computer Science and Game Theory · Computer Science 2023-12-22 Nils Bertschinger , Martin Hoefer , Daniel Schmand

We study potential games on unimodular random graphs of bounded degree, where players interact through the underlying network. Using the unimodular measure, we define a well-posed global potential that captures both finite- and…

Optimization and Control · Mathematics 2026-04-17 Eyal Neuman , Sturmius Tuschmann

To what extent does the structure of the players' strategy space influence the efficiency of decentralized solutions in congestion games? In this work, we investigate whether better performance are possible when restricting to load…

Computer Science and Game Theory · Computer Science 2022-02-25 Vittorio Bilò , Cosimo Vinci

In stochastic Nash equilibrium problems (SNEPs), it is natural for players to be uncertain about their complex environments and have multi-dimensional unknown parameters in their models. Among various SNEPs, this paper focuses on locally…

Optimization and Control · Mathematics 2022-04-06 Yuanhanqing Huang , Jianghai Hu

We study a class of non-cooperative aggregative games -- denoted as \emph{social purpose games} -- in which the payoffs depend separately on a player's own strategy (individual benefits) and on a function of the strategy profile which is…

Computer Science and Game Theory · Computer Science 2021-09-20 Robert P. Gilles , Lina Mallozzi , Roberta Messalli

This paper introduces a hierarchical framework for population games, where individuals delegate decision-making to proxies that act within their own strategic interests. This framework extends classical population games, where individuals…

Systems and Control · Electrical Eng. & Systems 2025-09-09 Yu-Wen Chen , Nuno C. Martins , Murat Arcak

Strategic interactions can be represented more concisely, and analyzed and solved more efficiently, if we are aware of the symmetries within the multiagent system. Symmetries also have conceptual implications, for example for equilibrium…

Computer Science and Game Theory · Computer Science 2025-03-03 Emanuel Tewolde , Brian Hu Zhang , Caspar Oesterheld , Tuomas Sandholm , Vincent Conitzer

Individual behaviors play an essential role in the dynamics of transmission of infectious diseases, including COVID--19. This paper studies a dynamic game model that describes the social distancing behaviors during an epidemic, assuming a…

Computer Science and Game Theory · Computer Science 2021-05-27 Ioannis Kordonis , Athanasios-Rafail Lagos , George P. Papavassilopoulos

We propose a new framework of Markov $\alpha$-potential games to study Markov games. We show that any Markov game with finite-state and finite-action is a Markov $\alpha$-potential game, and establish the existence of an associated…

Computer Science and Game Theory · Computer Science 2025-04-02 Xin Guo , Xinyu Li , Chinmay Maheshwari , Shankar Sastry , Manxi Wu

In this paper, we study an exponentiated multiplicative weights dynamic based on Hedge, a well-known algorithm in theoretical machine learning and algorithmic game theory. The empirical average (arithmetic mean) of the iterates Hedge…

Computer Science and Game Theory · Computer Science 2023-04-07 Ioannis Avramopoulos
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