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Related papers: Distributionally Robust Game Theory

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This paper introduces risk-revising players to a class of games with incomplete information. These players enter the game with ex ante risk preferences represented by coherent risk measures and develop time-consistent interim revisions of…

Optimization and Control · Mathematics 2026-03-23 Shutian Liu

We consider a two-player game of war of attrition under complete information. It is well-known that this class of games admits equilibria in pure, as well as mixed strategies, and much of the literature has focused on the latter. We show…

Optimization and Control · Mathematics 2021-11-30 George Georgiadis , Youngsoo Kim , H. Dharma Kwon

The distributed computation of a Nash equilibrium in aggregative games is gaining increased traction in recent years. Of particular interest is the mediator-free scenario where individual players only access or observe the decisions of…

Computer Science and Game Theory · Computer Science 2023-06-26 Yongqiang Wang , Angelia Nedich

We investigate the existence of certain types of equilibria (Nash, $\varepsilon$-Nash, subgame perfect, $\varepsilon$-subgame perfect, Pareto-optimal) in multi-player multi-outcome infinite sequential games. We use two fundamental…

Logic in Computer Science · Computer Science 2016-03-18 Stéphane Le Roux , Arno Pauly

Motivated by the sequence form formulation of Koller et al. (GEB'96), this paper defines {\em bilinear games}, and proposes efficient algorithms for its rank based subclasses. Bilinear games are two-player non-cooperative single-shot games…

Computer Science and Game Theory · Computer Science 2011-09-29 Jugal Garg , Albert Xin Jiang , Ruta Mehta

We motivate and propose a new model for non-cooperative Markov game which considers the interactions of risk-aware players. This model characterizes the time-consistent dynamic "risk" from both stochastic state transitions (inherent to the…

Computer Science and Game Theory · Computer Science 2019-11-22 Wenjie Huang , Pham Viet Hai , William B. Haskell

Bayesian regression games are a special class of two-player general-sum Bayesian games in which the learner is partially informed about the adversary's objective through a Bayesian prior. This formulation captures the uncertainty in regard…

Machine Learning · Computer Science 2021-10-04 Wenshuo Guo , Michael I. Jordan , Tianyi Lin

This paper focuses on finite-player incomplete information games where players may hold mutually inconsistent beliefs without a common prior. We introduce absolute continuity of beliefs, extending the classical notion of absolutely…

Theoretical Economics · Economics 2025-12-02 Denis Kojevnikov , Kyungchul Song

We consider the problem of decentralized power allocation for competitive rate-maximization in a frequency-selective Gaussian interference channel under bounded channel uncertainty. We formulate a distribution-free robust framework for the…

Information Theory · Computer Science 2015-03-17 Amod J. G. Anandkumar , Animashree Anandkumar , Sangarapillai Lambotharan , Jonathon A. Chambers

This study investigates differential games with motion-payoff uncertainty in continuous-time settings. We propose a framework where players update their beliefs about uncertain parameters using continuous Bayesian updating. Theoretical…

Multiagent Systems · Computer Science 2025-09-16 Jiangjing Zhou , Ovanes Petrosian , Ye Zhang , Hongwei Gao

Model-based algorithms -- algorithms that explore the environment through building and utilizing an estimated model -- are widely used in reinforcement learning practice and theoretically shown to achieve optimal sample efficiency for…

Machine Learning · Computer Science 2021-02-09 Qinghua Liu , Tiancheng Yu , Yu Bai , Chi Jin

Discrete-time replicator map is a prototype of evolutionary selection game dynamical models that have been very successful across disciplines in rendering insights into the attainment of the equilibrium outcomes, like the Nash equilibrium…

Populations and Evolution · Quantitative Biology 2021-02-22 Archan Mukhopadhyay , Sagar Chakraborty

A new solution concept for two-player zero-sum matrix games with multi-dimensional payoff is introduced. It is based on extensions of vector orders in K-dimensional spaces to order relations in their power sets, so-called set relations, and…

Optimization and Control · Mathematics 2017-01-31 Andreas H. Hamel , Andreas Loehne

We study finite normal-form games in which payoffs are subject to random perturbations and players face uncertainty about how these shocks co-move across actions, an ambiguity that naturally arises when only realized (not counterfactual)…

Theoretical Economics · Economics 2026-02-12 Yu Gui , Bahar Taşkesen

In this work, we study stochastic non-cooperative games, where only noisy black-box function evaluations are available to estimate the cost function for each player. Since each player's cost function depends on both its own decision…

Computer Science and Game Theory · Computer Science 2025-11-18 Haidong Li , Anzhi Sheng , Yijie Peng , Long Wang

Standard game theory assumes that the structure of the game is common knowledge among players. We relax this assumption by considering extensive games where agents may be unaware of the complete structure of the game. In particular, they…

Computer Science and Game Theory · Computer Science 2007-05-23 Joseph Y. Halpern , Leandro C. Rêgo

We use techniques from the statistical mechanics of disordered systems to analyse the properties of Nash equilibria of bimatrix games with large random payoff matrices. By means of an annealed bound, we calculate their number and analyse…

Disordered Systems and Neural Networks · Physics 2009-10-31 Johannes Berg , Martin Weigt

In imperfect information games (e.g. Bridge, Skat, Poker), one of the fundamental considerations is to infer the missing information while at the same time avoiding the disclosure of private information. Disregarding the issue of protecting…

Artificial Intelligence · Computer Science 2024-05-24 Jérôme Arjonilla , Abdallah Saffidine , Tristan Cazenave

In this article, we study a discounted stochastic game to model resource optimal intrusion detection in wireless sensor networks. To address the problem of uncertainties in various network parameters, we propose a globalized robust game…

Computer Science and Game Theory · Computer Science 2019-10-29 Debdas Ghosh , Akshay Sharma , K. K. Shukla

The known results regarding two-player zero-sum games are naturally generalized in complex space and are presented through a complete compact theory. The payoff function is defined by the real part of the payoff function in the real case,…

Optimization and Control · Mathematics 2022-11-30 Nick Dimou