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This work investigates a dynamic variant of Bayesian persuasion, in which a strategic sender seeks to influence a receiver's belief over time through controlling the timing of the information disclosure, under resource constraints. We…

Information Theory · Computer Science 2025-12-05 Ahmet Bugra Gundogan , Melih Bastopcu

Accurately predicting the outcome of sporting events has been a goal for many groups who seek to maximize profit. What makes this challenging is that the outcome of an event can be influenced by many factors that dynamically change across…

Applications · Statistics 2017-10-23 Erik J. Schlicht

The past two decades have seen a growing interest in combining causal information, commonly represented using causal graphs, with machine learning models. Probability trees provide a simple yet powerful alternative representation of causal…

Machine Learning · Computer Science 2022-05-18 Tue Herlau

Many legal cases require decisions about causality, responsibility or blame, and these may be based on statistical data. However, causal inferences from such data are beset by subtle conceptual and practical difficulties, and in general it…

Statistics Theory · Mathematics 2020-04-28 Philip Dawid , Monica Musio , Rossella Murtas

Information and free-energy maximization are physics principles that provide general rules for an agent to optimize actions in line with specific goals and policies. These principles are the building blocks for designing decision-making…

Machine Learning · Computer Science 2025-03-21 Alex Barbier-Chebbah , Christian L. Vestergaard , Jean-Baptiste Masson

This paper considers the use of observed and predicted match statistics as inputs to forecasts of the outcomes of football matches. It is shown that, were it possible to know the match statistics in advance, highly informative forecasts of…

Applications · Statistics 2020-01-27 Edward Wheatcroft

This article studies the value of information in route choice decisions when a fraction of players have access to high accuracy information about traffic incidents relative to others. To model such environments, we introduce a Bayesian…

Computer Science and Game Theory · Computer Science 2016-03-30 Jeffrey Liu , Saurabh Amin , Galina Schwartz

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

To take advantage of strategy commitment, a useful tactic of playing games, a leader must learn enough information about the follower's payoff function. However, this leaves the follower a chance to provide fake information and influence…

Computer Science and Game Theory · Computer Science 2023-06-14 Yurong Chen , Xiaotie Deng , Yuhao Li

Proper balance between exploitation and exploration is what makes good decisions, which achieve high rewards like payoff or evolutionary fitness. The Infomax principle postulates that maximization of information directs the function of…

Machine Learning · Computer Science 2016-05-25 Gautam Reddy , Antonio Celani , Massimo Vergassola

The marvel of markets lies in the fact that dispersed information is instantaneously processed and used to adjust the price of goods, services and assets. Financial markets are particularly efficient when it comes to processing information;…

Trading and Market Microstructure · Quantitative Finance 2018-07-19 Stefan Feuerriegel , Helmut Prendinger

We investigate the most popular approaches to the problem of sports betting investment based on modern portfolio theory and the Kelly criterion. We define the problem setting, the formal investment strategies, and review their common…

Portfolio Management · Quantitative Finance 2021-07-20 Matej Uhrín , Gustav Šourek , Ondřej Hubáček , Filip Železný

It is evidence that representation learning can improve model's performance over multiple downstream tasks in many real-world scenarios, such as image classification and recommender systems. Existing learning approaches rely on establishing…

Machine Learning · Computer Science 2022-02-18 Mengyue Yang , Xinyu Cai , Furui Liu , Xu Chen , Zhitang Chen , Jianye Hao , Jun Wang

We examine two types of binary betting markets, whose primary goal is for profit (such as sports gambling) or to gain information (such as prediction markets). We articulate the interplay between belief and price-setting to analyse both…

Computer Science and Game Theory · Computer Science 2024-06-07 Haiqing Zhu , Alexander Soen , Yun Kuen Cheung , Lexing Xie

Sports betting markets have grown very rapidly recently, with the total European gambling market worth 98.6 billion euro in 2019. Considering a high-resolution (1 Hz) data set provided by a large European bookmaker, we investigate the…

Physics and Society · Physics 2022-02-14 Marius Ötting , Rouven Michels , Roland Langrock , Christian Deutscher

The paper investigates the link between Granger causality graphs recently formalized by Eichler and directed information theory developed by Massey and Kramer. We particularly insist on the implication of two notions of causality that may…

Information Theory · Computer Science 2012-03-27 Pierre-Olivier Amblard , Olivier J. J. Michel

We consider a pair of traders in a market where the information available to the second trader is a strict subset of the information available to the first trader. The traders make prices based on the information available concerning a…

Mathematical Finance · Quantitative Finance 2024-01-24 George Bouzianis , Lane P. Hughston , Leandro Sánchez-Betancourt

With the vast amount of data collected on football and the growth of computing abilities, many games involving decision choices can be optimized. The underlying rule is the maximization of an expected utility of outcomes and the law of…

Machine Learning · Computer Science 2021-03-15 Preston Biro , Stephen G. Walker

Information in the form of data, which can be stored and transferred between users, can be viewed as an intangible commodity, which can be traded in exchange for money. Determining the fair price at which a string of data should be traded…

Statistical Mechanics · Physics 2024-09-11 Luca Gamberi , Alessia Annibale , Pierpaolo Vivo

Causality has traditionally been a scientific way to generate knowledge by relating causes to effects. From an imaginery point of view, causal graphs are a helpful tool for representing and infering new causal information. In previous…

Artificial Intelligence · Computer Science 2020-02-07 Eduardo C. Garrido-Merchán , C. Puente , A. Sobrino , J. A. Olivas