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Related papers: Game-Theoretic Upper Expectations for Discrete-Tim…

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We study the limit behaviour of upper and lower bounds on expected time averages in imprecise Markov chains; a generalised type of Markov chain where the local dynamics, traditionally characterised by transition probabilities, are now…

Probability · Mathematics 2021-02-10 Natan T'Joens , Jasper De Bock

Stochastic two-player games model systems with an environment that is both adversarial and stochastic. In this paper, we study the expected value of bounded quantitative prefix-independent objectives in the context of stochastic games. We…

Computer Science and Game Theory · Computer Science 2025-08-01 Laurent Doyen , Pranshu Gaba , Shibashis Guha

When a prediction algorithm serves a collection of users, disparities in prediction quality are likely to emerge. If users respond to accurate predictions by increasing engagement, inviting friends, or adopting trends, repeated learning…

Machine Learning · Computer Science 2025-11-27 Eden Saig , Nir Rosenfeld

In this paper we focus on noncooperative games with uncertain constraints coupling the agents' decisions. We consider a setting where bounded deviations of agents' decisions from the equilibrium are possible, and uncertain constraints are…

Optimization and Control · Mathematics 2023-11-28 George Pantazis , Filiberto Fele , Kostas Margellos

We give a unified treatment of the convergence of random series and the rate of convergence of strong law of large numbers in the framework of game-theoretic probability of Shafer and Vovk (2001). We consider games with the quadratic hedge…

Probability · Mathematics 2011-11-23 Kenshi Miyabe , Akimichi Takemura

We present a novel approach for explaining Gaussian processes (GPs) that can utilize the full analytical covariance structure present in GPs. Our method is based on the popular solution concept of Shapley values extended to stochastic…

Machine Learning · Statistics 2023-05-25 Siu Lun Chau , Krikamol Muandet , Dino Sejdinovic

We present an approach for systematically anticipating the actions and policies employed by \emph{oblivious} environments in concurrent stochastic games, while maximizing a reward function. Our main contribution lies in the synthesis of a…

Artificial Intelligence · Computer Science 2024-09-19 Shadi Tasdighi Kalat , Sriram Sankaranarayanan , Ashutosh Trivedi

We extend the quantitative synthesis framework by going beyond the worst-case. On the one hand, classical analysis of two-player games involves an adversary (modeling the environment of the system) which is purely antagonistic and asks for…

Computer Science and Game Theory · Computer Science 2015-11-02 Véronique Bruyère , Emmanuel Filiot , Mickael Randour , Jean-François Raskin

Conventional noncooperative game theory hypothesizes that the joint strategy of a set of players in a game must satisfy an "equilibrium concept". All other joint strategies are considered impossible; the only issue is what equilibrium…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 David H. Wolpert

We consider multiplayer stochastic games in which the payoff of each player is a bounded and Borel-measurable function of the infinite play. By using a generalization of the technique of Martin (1998) and Maitra and Sudderth (1998), we show…

Optimization and Control · Mathematics 2022-08-26 János Flesch , Eilon Solan

Choice functions constitute a simple, direct and very general mathematical framework for modelling choice under uncertainty. In particular, they are able to represent the set-valued choices that typically arise from applying decision rules…

Artificial Intelligence · Computer Science 2018-06-05 Jasper De Bock , Gert de Cooman

We introduce a new formulation of asset trading games in continuous time in the framework of the game-theoretic probability established by Shafer and Vovk (Probability and Finance: It's Only a Game! (2001) Wiley). In our formulation, the…

Trading and Market Microstructure · Quantitative Finance 2010-01-13 Kei Takeuchi , Masayuki Kumon , Akimichi Takemura

The paper addresses the problem of computing maximal conditional expected accumulated rewards until reaching a target state (briefly called maximal conditional expectations) in finite-state Markov decision processes where the condition is…

Logic in Computer Science · Computer Science 2023-03-07 Christel Baier , Joachim Klein , Sascha Klüppelholz , Sascha Wunderlich

Noncooperative games with uncertain payoffs have been classically studied under the expected-utility theory framework, which relies on the strong assumption that agents behave rationally. However, simple experiments on human decision makers…

Computer Science and Game Theory · Computer Science 2025-08-14 Ashok Krishnan K. S. , Hélène Le Cadre , Ana Bušić

Safe anytime-valid inference (SAVI) provides measures of statistical evidence and certainty -- e-processes for testing and confidence sequences for estimation -- that remain valid at all stopping times, accommodating continuous monitoring…

Statistics Theory · Mathematics 2023-06-21 Aaditya Ramdas , Peter Grünwald , Vladimir Vovk , Glenn Shafer

A stochastic model for behavioral changes by imitative pair interactions of individuals is developed. `Microscopic' assumptions on the specific form of the imitative processes lead to a stochastic version of the game dynamical equations.…

Statistical Mechanics · Physics 2007-05-23 Dirk Helbing

This paper considers the problem of constructing a confidence sequence, which is a sequence of confidence intervals that hold uniformly over time, for estimating the mean of bounded real-valued random processes. This paper revisits the…

Probability · Mathematics 2024-08-27 J. Jon Ryu , Alankrita Bhatt

We consider strong law of large numbers (SLLN) in the framework of game-theoretic probability of Shafer and Vovk (2001). We prove several versions of SLLN for the case that Reality's moves are unbounded. Our game-theoretic versions of SLLN…

Probability · Mathematics 2007-08-27 Masayuki Kumon , Akimichi Takemura , Kei Takeuchi

Cooperative interval game is a cooperative game in which every coalition gets assigned some closed real interval. This models uncertainty about how much the members of a coalition get for cooperating together. In this paper we study…

Computer Science and Game Theory · Computer Science 2018-11-12 Jan Bok

Every observation may follow a distribution that is randomly selected in a class of distributions. It is called the distribution uncertainty. This is a fact acknowledged in some research fields such as financial risk measure. Thus, the…

Methodology · Statistics 2014-12-10 Lu Lin , Ping Dong , Yunquan Song , Lixing Zhu