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Here we focus on the description of the mechanisms behind the process of information aggregation and decision making, a basic step to understand emergent phenomena in society, such as trends, information spreading or the wisdom of crowds.…

Physics and Society · Physics 2015-04-15 Víctor M. Eguíluz , N. Masuda , J. Fernández-Gracia

Suppose we have a pair of information channels, $\kappa_{1},\kappa_{2}$, with a common input. The Blackwell order is a partial order over channels that compares $\kappa_{1}$ and $\kappa_{2}$ by the maximal expected utility an agent can…

Information Theory · Computer Science 2017-11-13 Johannes Rauh , Pradeep Kr. Banerjee , Eckehard Olbrich , Jürgen Jost , Nils Bertschinger , David Wolpert

This paper presents and discusses several methods for reasoning from inconsistent knowledge bases. A so-called argumentative-consequence relation taking into account the existence of consistent arguments in favor of a conclusion and the…

Artificial Intelligence · Computer Science 2013-03-08 Salem Benferhat , Didier Dubois , Henri Prade

We try to establish a unified information theoretic approach to learning and to explore some of its applications. First, we define {\em predictive information} as the mutual information between the past and the future of a time series,…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Ilya Nemenman

We introduce a scalable Bayesian preference learning method for identifying convincing arguments in the absence of gold-standard rat- ings or rankings. In contrast to previous work, we avoid the need for separate methods to perform quality…

Computation and Language · Computer Science 2018-06-08 Edwin Simpson , Iryna Gurevych

Consider a random sample $X_1 , X_2 , ..., X_n$ drawn independently and identically distributed from some known sampling distribution $P_X$. Let $X_{(1)} \le X_{(2)} \le ... \le X_{(n)}$ represent the order statistics of the sample. The…

Information Theory · Computer Science 2020-09-28 Alex Dytso , Martina Cardone , Cynthia Rush

Experiments on decision making under uncertainty are known to display a classical pattern of risk aversion and risk seeking referred to as "fourfold pattern" (or "reflection effect") , but recent experiments varying the speed and order of…

Neurons and Cognition · Quantitative Biology 2024-01-17 Francesco Fumarola , Lukasz Kusmierz , Ronald B. Dekker

We propose indifference pricing to estimate the value of the weak information. Our framework allows for tractability, quantifying the amount of additional information, and permits the description of the smallness and the stability with…

Mathematical Finance · Quantitative Finance 2024-08-06 Fabrice Baudoin , Oleksii Mostovyi

In mathematics information is a number that measures uncertainty (entropy) based on a probabilistic distribution, often of an obscure origin. In real life language information is a datum, a statement, more precisely, a formula. But such a…

Artificial Intelligence · Computer Science 2022-05-17 Anatol Slissenko

A time-reversed dynamics unwinds information scrambling, which is induced during the time-forward evolution with a complex Hamiltonian. We show that if the scrambled information is, in addition, partially damaged by a local measurement,…

Quantum Physics · Physics 2020-07-27 Bin Yan , Nikolai A. Sinitsyn

Motivated by certain applications from physics, biochemistry, economics, and computer science, in which the objects under investigation are not accessible because of various limitations, we propose a trial-and-error model to examine…

Computational Complexity · Computer Science 2013-04-19 Xiaohui Bei , Ning Chen , Shengyu Zhang

Many representation schemes combining first-order logic and probability have been proposed in recent years. Progress in unifying logical and probabilistic inference has been slower. Existing methods are mainly variants of lifted variable…

Artificial Intelligence · Computer Science 2012-02-20 Vibhav Gogate , Pedro Domingos

These lectures deal with the problem of inductive inference, that is, the problem of reasoning under conditions of incomplete information. Is there a general method for handling uncertainty? Or, at least, are there rules that could in…

Data Analysis, Statistics and Probability · Physics 2016-09-08 Ariel Caticha

We show that strategies implemented in automatic theorem proving involve an interesting tradeoff between execution speed, proving speedup/computational time and usefulness of information. We advance formal definitions for these concepts by…

Logic in Computer Science · Computer Science 2015-06-16 Santiago Hernández-Orozco , Francisco Hernández-Quiroz , Hector Zenil , Wilfried Sieg

Traditional machine learning relies on explicit models and domain assumptions, limiting flexibility and interpretability. We introduce a model-free framework using surprisal (information theoretic uncertainty) to directly analyze and…

We study belief revision when information is represented by a set of probability distributions, or general information. General information extends the standard event notion while including qualitative information (A is more likely than B),…

Theoretical Economics · Economics 2025-02-04 Adam Dominiak , Matthew Kovach , Gerelt Tserenjigmid

We propose predictive information, that is information between a long past of duration T and the entire infinitely long future of a time series, as a universal order parameter to study phase transitions in physical systems. It can be used,…

Statistical Mechanics · Physics 2014-02-04 Martin Tchernookov , Ilya Nemenman

This paper studies a game in which an informed sender with state-independent preferences uses verifiable messages to convince a receiver to choose an action from a finite set. We characterize the equilibrium outcomes of the game and compare…

Theoretical Economics · Economics 2025-10-10 Maria Titova , Kun Zhang

We prove oracle inequalities for a penalized log-likelihood criterion that hold even if the data are not independent and not stationary, based on a martingale approach. The assumptions are checked for various contexts: density estimation…

Statistics Theory · Mathematics 2024-05-20 Julien Aubert , Luc Lehéricy , Patricia Reynaud-Bouret

This technical report provides the supplementary material for a paper entitled "Information based clustering", to appear shortly in Proceedings of the National Academy of Sciences (USA). In Section I we present in detail the iterative…

Quantitative Methods · Quantitative Biology 2009-09-29 Noam Slonim , Gurinder Singh Atwal , Gasper Tkacik , William Bialek