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An instability property of the Birkhoff's ergodic theorem and related asymptotic laws with respect to small violations of algorithmic randomness is studied. The Shannon--McMillan--Breiman theorem and all universal compression schemes are…

Information Theory · Computer Science 2012-07-26 Vladimir V'yugin

The idea of a parsing of a stationary process according to a collection of words is introduced, and the basic framework required for the asymptotic analysis of these parsings is presented. We demonstrate how the pointwise ergodic theorem…

Dynamical Systems · Mathematics 2025-02-13 Matan Tal

The maximum entropy principle (MEP) is a method for obtaining the most likely distribution functions of observables from statistical systems, by maximizing entropy under constraints. The MEP has found hundreds of applications in ergodic and…

Classical Physics · Physics 2016-10-03 Rudolf Hanel , Stefan Thurner , Murray Gell-Mann

The Shannon-McMillan-Breiman theorem is one of the most important results in information theory, which can describe the random ergodic process, and its proof uses the famous Birkhoff ergodic theorem, so it can be seen that it plays a…

Dynamical Systems · Mathematics 2025-06-03 Yuan Lian , Bin Zhu

We propose a method to derive the stationary size distributions of a system, and the degree distributions of networks, using maximisation of the Gibbs-Shannon entropy. We apply this to a preferential attachment-type algorithm for systems of…

Physics and Society · Physics 2020-03-17 Cornelia Metzig , Caroline Colijn

We study two-player (zero-sum) concurrent mean-payoff games played on a finite-state graph. We focus on the important sub-class of ergodic games where all states are visited infinitely often with probability 1. The algorithmic study of…

Computer Science and Game Theory · Computer Science 2014-04-24 Krishnendu Chatterjee , Rasmus Ibsen-Jensen

Predictive inference requires balancing statistical accuracy against informational complexity, yet the choice of complexity measure is usually imposed rather than derived. We treat econometric objects as predictive rules, mappings from…

Statistics Theory · Mathematics 2026-02-16 Nicholas G. Polson , Daniel Zantedeschi

It is known that a gambler repeating a game with positive expected value has a positive probability to never go broke. We use the mass transport method to prove the generalization of this fact where the gains from the bets form a…

Probability · Mathematics 2022-03-21 Calvin Wooyoung Chin

The theorem of Shannon-McMillan-Breiman states that for every generating partition on an ergodic system, the exponential decay rate of the measure of cylinder sets equals the metric entropy almost everywhere (provided the entropy is…

Dynamical Systems · Mathematics 2009-03-10 Nicolai T A Haydn

Four estimators of the directed information rate between a pair of jointly stationary ergodic finite-alphabet processes are proposed, based on universal probability assignments. The first one is a Shannon--McMillan--Breiman type estimator,…

Information Theory · Computer Science 2016-11-15 Jiantao Jiao , Haim H. Permuter , Lei Zhao , Young-Han Kim , Tsachy Weissman

We introduce the notion of common conditional expectation to investigate Birkhoff's ergodic theorem and subadditive ergodic theorem for invariant upper probabilities. If in addition, the upper probability is ergodic, we construct an…

Probability · Mathematics 2024-11-04 Chunrong Feng , Wen Huang , Chunlin Liu , Huaizhong Zhao

In this paper, we consider contention resolution algorithms that are augmented with predictions about the network. We begin by studying the natural setup in which the algorithm is provided a distribution defined over the possible network…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-05-27 Seth Gilbert , Calvin Newport , Nitin Vaidya , Alex Weaver

In this paper, I expand Shannon's definition of entropy into a new form of entropy that allows integration of information from different random events. Shannon's notion of entropy is a special case of my more general definition of entropy.…

Machine Learning · Computer Science 2008-11-04 Stefan Jaeger

We develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to…

Computer Science and Game Theory · Computer Science 2024-11-12 Xavier Allamigeon , Stéphane Gaubert , Ricardo D. Katz , Mateusz Skomra

We study the relations between the recently proposed machine-independent quantum complexity of P. Gacs~\cite{Gacs} and the entropy of classical and quantum systems. On one hand, by restricting Gacs complexity to ergodic classical dynamical…

Information Theory · Computer Science 2018-04-23 Fabio Benatti , Samad Khabbazi Oskouei , Ahmad Shafiei Deh Abad

We describe and develop a close relationship between two problems that have customarily been regarded as distinct: that of maximizing entropy, and that of minimizing worst-case expected loss. Using a formulation grounded in the equilibrium…

Statistics Theory · Mathematics 2007-06-13 Peter D. Grunwald , A. Philip Dawid

The ergodic hypothesis is examined for energetically open fluid systems represented by the barotropic Navier--Stokes equations with general inflow/outflow boundary conditions. We show that any globally bounded trajectory generates a…

Analysis of PDEs · Mathematics 2021-05-19 Francesco Fanelli , Eduard Feireisl , Martina Hofmanová

We introduce a new isomorphism-invariant notion of entropy for measure preserving actions of arbitrary countable groups on probability spaces, which we call orbital Rokhlin entropy. It employs Danilenko's orbital approach to entropy of a…

Dynamical Systems · Mathematics 2019-03-14 Amos Nevo , Felix Pogorzelski

Shannon entropy, a cornerstone of information theory, statistical physics and inference methods, is uniquely identified by the Shannon-Khinchin or Shore-Johnson axioms. Generalizations of Shannon entropy, motivated by the study of…

Data Analysis, Statistics and Probability · Physics 2026-04-20 Andrea Somazzi , Diego Garlaschelli

We study zero-sum games in the space of probability distributions over the Euclidean space $\mathbb{R}^d$ with entropy regularization, in the setting when the interaction function between the players is smooth and strongly convex-strongly…

Computer Science and Game Theory · Computer Science 2025-07-01 Yang Cai , Siddharth Mitra , Xiuyuan Wang , Andre Wibisono
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