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We study online fair division when there are a finite number of item types and the player values for the items are drawn randomly from distributions with unknown means. In this setting, a sequence of indivisible items arrives according to a…

Computer Science and Game Theory · Computer Science 2025-01-14 Benjamin Schiffer , Shirley Zhang

We consider the problem of testing the mean of a bounded real random variable. We introduce a notion of optimal classes for e-variables and e-processes, and establish the optimality of the coin-betting formulation among e-variable-based…

Statistics Theory · Mathematics 2026-05-08 Eugenio Clerico

MiBoard (Multiplayer Interactive Board Game) is an online, turnbased board game that was developed to assess the integration of game characteristics (point rewards, game-like interaction, and peer feedback) and how that might affect student…

Computer Science and Game Theory · Computer Science 2010-09-14 Justin F. Brunelle , G. Tanner Jackson , Kyle Dempsey , Chutima Boonthum , Irwin B. Levinstein , Danielle S. McNamara

In two-player zero-sum stochastic games, where two competing players make decisions under uncertainty, a pair of optimal strategies is traditionally described by Nash equilibrium and computed under the assumption that the players have…

Optimization and Control · Mathematics 2019-07-30 Yagiz Savas , Mohamadreza Ahmadi , Takashi Tanaka , Ufuk Topcu

Parity games are abstract infinite-round games that take an important role in formal verification. In the basic setting, these games are two-player, turn-based, and played under perfect information on directed graphs, whose nodes are…

Computer Science and Game Theory · Computer Science 2019-10-31 Antonio Di Stasio , Aniello Murano , Giuseppe Perelli , Moshe Y. Vardi

This paper develops an algorithm for upper- and lower-bounding the value function for a class of linear time-varying games subject to convex control sets. In particular, a two-player zero-sum differential game is considered where the…

Optimization and Control · Mathematics 2025-03-12 Vincent Liu , Chris Manzie , Peter M. Dower

In the context of supervised parametric models, we introduce the concept of e-values. An e-value is a scalar quantity that represents the proximity of the sampling distribution of parameter estimates in a model trained on a subset of…

Machine Learning · Statistics 2022-07-19 Subhabrata Majumdar , Snigdhansu Chatterjee

In this paper, we study one-player and two-player energy mean-payoff games. Energy mean-payoff games are games of infinite duration played on a finite graph with edges labeled by 2-dimensional weight vectors. The objective of the first…

Computer Science and Game Theory · Computer Science 2019-07-03 Véronique Bruyère , Quentin Hautem , Mickael Randour , Jean-François Raskin

In this paper we introduce the novel framework of distributionally robust games. These are multi-player games where each player models the state of nature using a worst-case distribution, also called adversarial distribution. Thus each…

Optimization and Control · Mathematics 2017-07-25 Dario Bauso , Jian Gao , Hamidou Tembine

Parity games are games that are played on directed graphs whose vertices are labeled by natural numbers, called priorities. The players push a token along the edges of the digraph. The winner is determined by the parity of the greatest…

Computer Science and Game Theory · Computer Science 2015-03-20 Christoph Dittmann , Stephan Kreutzer , Alexandru I. Tomescu

Consider $N$ players and $K$ games taking place simultaneously. Each of these games is modeled as a Tug-of-War (ToW) game where increasing the action of one player decreases the reward for all other players. Each player participates in only…

Computer Science and Game Theory · Computer Science 2026-04-14 Siddharth Chandak , Ilai Bistritz , Nicholas Bambos

We consider zero-sum stochastic games with perfect information and finitely many states and actions. The payoff is computed by a function which associates to each infinite sequence of states and actions a real number. We prove that if the…

Computer Science and Game Theory · Computer Science 2022-03-29 Hugo Gimbert , Edon Kelmendi

The McNaughton-Zielonka divide et impera algorithm is the simplest and most flexible approach available in the literature for determining the winner in a parity game. Despite its theoretical worst-case complexity and the negative reputation…

Logic in Computer Science · Computer Science 2017-09-08 Massimo Benerecetti , Daniele Dell'Erba , Fabio Mogavero

A knockout tournament is one of the most simple and popular forms of competition. Here, we are given a binary tournament tree where all leaves are labeled with seed position names. The players participating in the tournament are assigned to…

Discrete Mathematics · Computer Science 2025-06-05 Klim Efremenko , Hendrik Molter , Meirav Zehavi

The numbers game is a one-player game played on a finite simple graph with certain ``amplitudes'' assigned to its edges and with an initial assignment of real numbers to its nodes. The moves of the game successively transform the numbers at…

Combinatorics · Mathematics 2007-10-02 Robert G. Donnelly

This paper describes a new algorithm for decision making in two-player real-time video games. As with Monte Carlo Tree Search, the algorithm can be used without heuristics and has been developed for use in general video game AI. The…

Artificial Intelligence · Computer Science 2016-07-07 Jialin Liu , Diego Pérez-Liébana , Simon M. Lucas

In networking and computing, resource allocation is typically addressed using classical sharing protocols as, for instance, the proportional division rule, the max-min fair allocation , or other solutions inspired by cooperative game…

Networking and Internet Architecture · Computer Science 2017-04-25 Francesca Fossati , Stefano Moretti , Stefano Secci

Traditional coding theory guarantees valid decoding only if a minority of symbols are adversarially manipulated. In contrast, the game of coding framework ensures reliable decoding, even in the presence of an adversarial majority. This…

Information Theory · Computer Science 2026-04-13 Hanzaleh Akbari Nodehi , Parsa Moradi , Soheil Mohajer , Mohammad Ali Maddah-Ali

Most learning algorithms are not invariant to the scale of the function that is being approximated. We propose to adaptively normalize the targets used in learning. This is useful in value-based reinforcement learning, where the magnitude…

Machine Learning · Computer Science 2016-08-17 Hado van Hasselt , Arthur Guez , Matteo Hessel , Volodymyr Mnih , David Silver

A competitive market is modeled as a game of incomplete information. One player observes some payoff-relevant state and can sell (possibly noisy) messages thereof to the other, whose willingness to pay is contingent on their own beliefs. We…

Computer Science and Game Theory · Computer Science 2025-05-02 Thomas Falconer , Anubhav Ratha , Jalal Kazempour , Pierre Pinson , Maryam Kamgarpour