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Given a skew-symmetric matrix, the corresponding two-player symmetric zero-sum game is defined as follows: one player, the row player, chooses a row and the other player, the column player, chooses a column. The payoff of the row player is…

Computer Science and Game Theory · Computer Science 2017-07-11 Florian Brandl

The strategies adopted by individuals to select relevant information to pass on are central to understanding problem solving by groups. Here we use agent-based simulations to revisit a cooperative problem-solving scenario where the task is…

Multiagent Systems · Computer Science 2019-05-21 Sandro M. Reia , Paulo F. Gomes , José F. Fontanari

Cooperative behavior, where one individual incurs a cost to help another, is a wide spread phenomenon. Here we study direct reciprocity in the context of the alternating Prisoner's Dilemma. We consider all strategies that can be implemented…

Populations and Evolution · Quantitative Biology 2014-03-05 Benjamin M. Zagorsky , Johannes G. Reiter , Krishnendu Chatterjee , Martin A. Nowak

The exponential ordering is exploited in the context of non-auto\-no\-mous delay systems, inducing monotone skew-product semiflows under less restrictive conditions than usual. Some dynamical concepts linked to the order, such as…

Dynamical Systems · Mathematics 2022-12-09 Sylvia Novo , Rafael Obaya , Ana M. Sanz , Victor M. Villarragut

Stackelberg games have been widely used to model interactive decision-making problems in a variety of domains such as energy systems, transportation, cybersecurity, and human-robot interaction. However, existing algorithms for solving…

Optimization and Control · Mathematics 2023-03-14 Yansong Li , Shuo Han

Although influence maximization problem has been extensively studied over the past ten years, majority of existing work adopt one of the following models: \emph{full-feedback model} or \emph{zero-feedback model}. In the zero-feedback model,…

Social and Information Networks · Computer Science 2019-04-23 Jing Yuan , Shaojie Tang

No-regret learners seek to minimize the difference between the loss they cumulated through the actions they played, and the loss they would have cumulated in hindsight had they consistently modified their behavior according to some strategy…

Computer Science and Game Theory · Computer Science 2023-11-09 Gabriele Farina , Charilaos Pipis

Will the strategy of resetting} help a stochastic process to reach its target efficiently, with its environment continually toggling between a strongly favourable and an unfavourable (or weakly favourable) state? A diffusive run-and-tumble…

Statistical Mechanics · Physics 2025-03-04 Hillol kumar Barman , Amitabha Nandi , Dibyendu Das

Guessing games for directed graphs were introduced by Riis for studying multiple unicast network coding problems. In a guessing game, the players toss generalised dice and can see some of the other outcomes depending on the structure of an…

Information Theory · Computer Science 2014-11-04 Rahil Baber , Demetres Christofides , Anh N. Dang , Søren Riis , Emil Vaughan

We investigate the mathematics behind unshuffles, a type of card shuffle closely related to classical perfect shuffles. To perform an unshuffle, deal all the cards alternately into two piles and then stack the one pile on top of the other.…

Combinatorics · Mathematics 2024-10-09 Cornelia A. Van Cott , Katie Wang

We consider a simple optimal probabilistic problem solving strategy that searches through potential solution candidates in a specific order. We are interested in what impact has interchanging the order of two solution candidates with…

Optimization and Control · Mathematics 2016-12-01 Frantisek Duris

We investigate the calibration of estimations to increase performance with an optimal monotone transform on the estimator outputs. We start by studying the traditional square error setting with its weighted variant and show that the optimal…

Machine Learning · Computer Science 2021-11-02 Kaan Gokcesu , Hakan Gokcesu

Linear system games are a generalization of Mermin's magic square game introduced by Cleve and Mittal. They show that perfect strategies for linear system games in the tensor-product model of entanglement correspond to finite-dimensional…

Quantum Physics · Physics 2017-02-01 Richard Cleve , Li Liu , William Slofstra

Surprise-based learning allows agents to rapidly adapt to non-stationary stochastic environments characterized by sudden changes. We show that exact Bayesian inference in a hierarchical model gives rise to a surprise-modulated trade-off…

Machine Learning · Statistics 2020-09-25 Vasiliki Liakoni , Alireza Modirshanechi , Wulfram Gerstner , Johanni Brea

Stochastic games have become a prevalent framework for studying long-term multi-agent interactions, especially in the context of multi-agent reinforcement learning. In this work, we comprehensively investigate the concept of constant-memory…

Computer Science and Game Theory · Computer Science 2025-10-16 Fengming Zhu , Fangzhen Lin

Motivated by programmatic advertising optimization, we consider the task of sequentially allocating budget across a set of resources. At every time step, a feasible allocation is chosen and only a corresponding random return is observed.…

Artificial Intelligence · Computer Science 2024-10-02 Juliette Achddou , Olivier Cappe , Aurélien Garivier

We propose two new alternating direction methods to solve "fully" nonsmooth constrained convex problems. Our algorithms have the best known worst-case iteration-complexity guarantee under mild assumptions for both the objective residual and…

Optimization and Control · Mathematics 2018-01-16 Quoc Tran-Dinh , Volkan Cevher

In this paper, we consider the problem of guessing a sequence subject to a distortion constraint. Specifically, we assume the following game between Alice and Bob: Alice has a sequence $\bx$ of length $n$. Bob wishes to guess $\bx$, yet he…

Information Theory · Computer Science 2021-12-28 Asaf Cohen , Neri Merhav

We study a variation of the game of best choice (also known as the secretary problem or game of googol) under an additional assumption that the ranks of interview candidates are restricted using permutation pattern-avoidance. We describe…

Combinatorics · Mathematics 2019-04-24 Aaron Fowlkes , Brant Jones

We study the performance of stochastic gradient descent (SGD) on smooth and strongly-convex finite-sum optimization problems. In contrast to the majority of existing theoretical works, which assume that individual functions are sampled with…

Machine Learning · Computer Science 2021-06-03 Itay Safran , Ohad Shamir