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We here adopt Bayesian nonparametric mixture models to extend multi-armed bandits in general, and Thompson sampling in particular, to scenarios where there is reward model uncertainty. In the stochastic multi-armed bandit, the reward for…

Machine Learning · Statistics 2022-08-26 Iñigo Urteaga , Chris H. Wiggins

In social situations with which evolutionary game is concerned, individuals are considered to be heterogeneous in various aspects. In particular, they may differently perceive the same outcome of the game owing to heterogeneity in…

Populations and Evolution · Quantitative Biology 2014-03-07 Naoki Masuda

In repeated games, strategies are often evaluated by their ability to guarantee the performance of the single best action that is selected in hindsight, a property referred to as \emph{Hannan consistency}, or \emph{no-regret}. However, the…

Computer Science and Game Theory · Computer Science 2025-01-24 Ludovico Crippa , Yonatan Gur , Bar Light

The existence of simple, uncoupled no-regret dynamics that converge to correlated equilibria in normal-form games is a celebrated result in the theory of multi-agent systems. Specifically, it has been known for more than 20 years that when…

Computer Science and Game Theory · Computer Science 2022-09-05 Andrea Celli , Alberto Marchesi , Gabriele Farina , Nicola Gatti

For discrete-valued time series, predictive inference cannot be implemented through the construction of prediction intervals to some predetermined coverage level, as this is the case for real-valued time series. To address this problem, we…

Methodology · Statistics 2025-07-23 Maxime Faymonville , Carsten Jentsch , Efstathios Paparoditis

Learning or estimating game models from data typically entails inducing separate models for each setting, even if the games are parametrically related. In empirical mechanism design, for example, this approach requires learning a new game…

Computer Science and Game Theory · Computer Science 2026-05-05 Madelyn Gatchel , Michael P. Wellman

Agents often have individual goals which depend on a group's actions. If agents trust a forecast of collective action and adapt strategically, such prediction can influence outcomes non-trivially, resulting in a form of performative…

Machine Learning · Computer Science 2025-02-18 António Góis , Mehrnaz Mofakhami , Fernando P. Santos , Gauthier Gidel , Simon Lacoste-Julien

Motivated by applications in cyber security, we develop a simple game model for describing how a learning agent's private information influences an observing agent's inference process. The model describes a situation in which one of the…

Computer Science and Game Theory · Computer Science 2019-09-16 Erik Miehling , Roy Dong , Cédric Langbort , Tamer Başar

We introduce a class of extensive form games where players might not be able to foresee the possible consequences of their decisions and form a model of their opponents which they exploit to achieve a more profitable outcome. We improve…

Artificial Intelligence · Computer Science 2016-05-31 Paolo Turrini

Game theory relies heavily on the availability of cardinal utility functions, but in fields such as matching markets, only ordinal preferences are typically elicited. The literature focuses on mechanisms with simple dominant strategies, but…

Computer Science and Game Theory · Computer Science 2024-08-22 Fabian R. Pieroth , Martin Bichler

Conventional game theory assumes that players are perfectly rational. In a realistic situation, however, players are rarely perfectly rational. This bounded rationality is one of the main reasons why the predictions of Nash equilibrium in…

Physics and Society · Physics 2026-01-01 Mojtaba Madadi Asl , Mehdi Sadeghi

An important challenge in non-cooperative game theory is coordinating on a single (approximate) equilibrium from many possibilities - a challenge that becomes even more complex when players hold private information. Recommender mechanisms…

Computer Science and Game Theory · Computer Science 2025-05-30 Bengisu Guresti , Chongjie Zhang , Yevgeniy Vorobeychik

This paper considers a zero-sum two-player asymmetric information stochastic game where only one player knows the system state, and the transition law is controlled by the informed player only. For the informed player, it has been shown…

Computer Science and Game Theory · Computer Science 2017-11-08 Lichun Li , Cedric Langbort , Jeff S. Shamma

How to estimate heterogeneity, e.g. the effect of some variable differing across observations, is a key question in political science. Methods for doing so make simplifying assumptions about the underlying nature of the heterogeneity to…

Methodology · Statistics 2021-03-31 Max Goplerud

This work lies in the fusion of experimental economics and data mining. It continues author's previous work on mining behaviour rules of human subjects from experimental data, where game-theoretic predictions partially fail to work.…

Computer Science and Game Theory · Computer Science 2012-11-13 Rustam Tagiew

We consider distributed learning problem in games with an unknown cost-relevant parameter, and aim to find the Nash equilibrium while learning the true parameter. Inspired by the social learning literature, we propose a distributed…

Optimization and Control · Mathematics 2023-03-14 Shijie Huang , Jinlong Lei , Yiguang Hong

Perceptions of political bias in the media are formed directly, through the independent consumption of the published outputs of a media organization, and indirectly, through observing the collective responses of political allies and…

Physics and Society · Physics 2022-06-28 Nicholas Kah Yean Low , Andrew Melatos

Statistical multispecies models of multiarea marine ecosystems use a variety of data sources to estimate parameters using composite or weighted likelihood functions with associated weighting issues and questions on how to obtain variance…

Applications · Statistics 2012-02-16 Lorna Taylor , Verena M. Trenkel , Vojtech Kupca , Gunnar Stefansson

Bayesian methods suffer from the problem of how to specify prior beliefs. One interesting idea is to consider worst-case priors. This requires solving a stochastic zero-sum game. In this paper, we extend well-known results from bandit…

Machine Learning · Computer Science 2014-12-11 Emmanouil G. Androulakis , Christos Dimitrakakis

Bayesian rationality in strategic games presumes that it is possible to translate strategic uncertainty into imperfect information. Correlated equilibrium is guided by the idea that players are Bayes rational, have a common prior, and…

Computer Science and Game Theory · Computer Science 2016-02-02 Gabriel Frahm