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Related papers: On Directed Information and Gambling

200 papers

We formulate an adaptive version of Kelly's horse model in which the gambler learns from past race results using Bayesian inference. A known asymptotic scaling for the difference between the growth rate of the gambler and the optimal growth…

Statistical Mechanics · Physics 2022-10-05 Armand Despons , David Lacoste , Luca Peliti

We study how cursedness, the tendency to neglect how other people's strategies depend on their private information, affects information transmission in Spence's job market signaling game. We characterize the Cursed Sequential Equilibrium…

General Economics · Economics 2025-04-25 Po-Hsuan Lin , Yen Ling Tan

In an intelligent transportation system, the effects and relations of traffic flow at different points in a network are valuable features which can be exploited for control system design and traffic forecasting. In this paper, we define the…

Systems and Control · Electrical Eng. & Systems 2020-11-24 Sina Molavipour , Germán Bassi , Mladen Čičić , Mikael Skoglund , Karl Henrik Johansson

Probabilities of causation are fundamental to individual-level explanation and decision making, yet they are inherently counterfactual and not point-identifiable from data in general. Existing bounds either disregard available covariates,…

Artificial Intelligence · Computer Science 2026-02-17 Yuxuan Xie , Ang Li

This paper seeks to clarify whether the processing of two types of messages that promote responsible gambling, namely personalized messages and normative messages, varies across gamblers severity habits and rational thinking

General Economics · Economics 2025-02-12 J. Sanchez-Fernandez , L. A. Casado-Aranda , I. Ozer , Nuria Hernandez-Vergara

We propose an extensive-form solution concept, with players that neglect information from hypothetical events, but make inferences from observed events. Our concept modifies cursed equilibrium (Eyster and Rabin, 2005), and allows that…

Theoretical Economics · Economics 2025-07-29 Shani Cohen , Shengwu Li

We identify the common underlying form of the capacity expression that is applicable to both cases where causal or non-causal side information is made available to the transmitter. Using this common form we find that for the single user…

Information Theory · Computer Science 2007-07-13 Syed A. Jafar

We consider the classical problem of discrete distribution estimation using i.i.d. samples in a novel scenario where additional side information is available on the distribution. In large alphabet datasets such as text corpora, such side…

Information Theory · Computer Science 2026-01-19 Haricharan Balasundaram , Andrew Thangaraj

This paper addresses the problem of inferring circulation of information between multiple stochastic processes. We discuss two possible frameworks in which the problem can be studied: directed information theory and Granger causality. The…

Information Theory · Computer Science 2011-11-02 Pierre-Olivier Amblard , Olivier J. J. Michel

Information asymmetry in games enables players with the information advantage to manipulate others' beliefs by strategically revealing information to other players. This work considers a double-sided information asymmetry in a Bayesian…

Computer Science and Game Theory · Computer Science 2023-08-29 Tao Li , Quanyan Zhu

We consider a specialized form of risk management for betting opportunities with low payout frequency, presented in particular for exotic horse race wagering. An optimization problem is developed which limits losing streaks with high…

Optimization and Control · Mathematics 2017-08-03 Antoine Deza , Kai Huang , Michael R. Metel

We propose information-directed sampling -- a new approach to online optimization problems in which a decision-maker must balance between exploration and exploitation while learning from partial feedback. Each action is sampled in a manner…

Machine Learning · Computer Science 2017-07-10 Daniel Russo , Benjamin Van Roy

Most betting market models employ static frameworks that condition decisions on final odds. Using a unique dataset of interim odds from Japanese horse racing, this study examines the validity of such static analyses by asking whether there…

General Economics · Economics 2025-09-19 Hiroaki Hanyu , Shunsuke Ishii , Suguru Otani , Kazuhiro Teramoto

We investigate the problem of gambling with uncertainty in outcome probabilities. Stochastic optimization models are proposed for optimal investing on events with mutually exclusive outcomes when probabilities are estimated using…

Optimization and Control · Mathematics 2017-08-03 Michael R. Metel

We establish fundamental connections between utility theories of wealth from the economic sciences and information-theoretic quantities. In particular, we introduce operational tasks based on betting where both gambler and bookmaker have…

Information Theory · Computer Science 2023-06-16 Andres F. Ducuara , Paul Skrzypczyk

When users lack specific knowledge of various system parameters, their uncertainty may lead them to make undesirable deviations in their decision making. To alleviate this, an informed system operator may elect to signal information to…

Computer Science and Game Theory · Computer Science 2023-03-31 Bryce L. Ferguson , Philip N. Brown , Jason R. Marden

Interaction information is one of the multivariate generalizations of mutual information, which expresses the amount information shared among a set of variables, beyond the information, which is shared in any proper subset of those…

Artificial Intelligence · Computer Science 2017-02-01 AmirEmad Ghassami , Negar Kiyavash

Every interaction of a living organism with its environment involves the placement of a bet. Armed with partial knowledge about a stochastic world, the organism must decide its next step or near-term strategy, an act that implicitly or…

Populations and Evolution · Quantitative Biology 2023-05-30 Philipp Fleig , Vijay Balasubramanian

Decision-making under uncertainty and causal thinking are fundamental aspects of intelligent reasoning. Decision-making has been well studied when the available information is considered at the associative (probabilistic) level. The…

Artificial Intelligence · Computer Science 2026-04-30 Mauricio Gonzalez Soto , David Danks , Hugo J. Escalante Balderas , L. Enrique Sucar

We consider the problem of decision-making with side information and unbounded loss functions. Inspired by probably approximately correct learning model, we use a slightly different model that incorporates the notion of side information in…

Machine Learning · Computer Science 2007-07-13 Majid Fozunbal , Ton Kalker