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Related papers: Generalized Interacting Urn Models

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We introduce a class of reinforcement models where, at each time step $t$, one first chooses a random subset $A_t$ of colours (independent of the past) from $n$ colours of balls, and then chooses a colour $i$ from this subset with…

Probability · Mathematics 2014-06-03 Remco van der Hofstad , Mark Holmes , Alexey Kuznetsov , Wioletta Ruszel

Consider the multicolored urn model where, after every draw, balls of the different colors are added to the urn in a proportion determined by a given stochastic replacement matrix. We consider some special replacement matrices which are not…

Probability · Mathematics 2009-02-09 Arup Bose , Amites Dasgupta , Krishanu Maulik

Adaptive randomly reinforced urn (ARRU) is a two-color urn model where the updating process is defined by a sequence of non-negative random vectors $\{(D_{1,n}, D_{2,n});n\geq1\}$ and randomly evolving thresholds which utilize accruing…

Probability · Mathematics 2019-09-27 Giacomo Aletti , Andrea Ghiglietti , Anand Vidyashankar

The generalized P\`olya urn (GPU) models and their variants have been investigated in several disciplines. However, typical assumptions made with respect to the GPU do not include urn models with diagonal replacement matrix, which arise in…

Probability · Mathematics 2015-02-24 Andrea Ghiglietti , Anand N. Vidyashankar , William F. Rosenberger

Consider an urn model whose replacement matrix is triangular, has all entries nonnegative and the row sums are all equal to one. We obtain the strong laws for the counts of balls corresponding to each color. The scalings for these laws…

Probability · Mathematics 2010-09-27 Arup Bose , Amites Dasgupta , Krishanu Maulik

We define and prove limit results for a class of dominant P\'olya sequences, which are randomly reinforced urn processes with color-specific random weights and unbounded number of possible colors. Under fairly mild assumptions on the…

Probability · Mathematics 2023-12-12 Hristo Sariev , Sandra Fortini , Sonia Petrone

Consider an urn containing balls labeled with integer values. Define a discrete-time random process by drawing two balls, one at a time and with replacement, and noting the labels. Add a new ball labeled with the sum of the two drawn…

Probability · Mathematics 2023-06-22 Mackenzie Simper

We prove a Gaussian process approximation for the sequence of random compositions of a two-color randomly reinforced urn for both the cases with the equal and unequal reinforcement means. By using the Gaussian approximation, the law of the…

Probability · Mathematics 2020-05-08 Li-Xin Zhang

The paper deals with the problem of finding the best alternatives on the basis of pairwise comparisons when these comparisons need not be transitive. In this setting, we study a reinforcement urn model. We prove convergence to the optimal…

Optimization and Control · Mathematics 2013-01-25 Benoit Laslier , Jean-Francois Laslier

An urn model of Diaconis and some generalizations are discussed. A convergence theorem is proved that implies for Diaconis' model that the empirical distribution of balls in the urn converges with probability one to the uniform…

Probability · Mathematics 2007-05-23 David Siegmund , Benjamin Yakir

We investigate a nonclassic urn model with triggers that increase the number of colors. The scheme has emerged as a model for web services that set up frequently asked questions (FAQ). We present a thorough asymptotic analysis of the FAQ…

Probability · Mathematics 2026-01-16 Irene Crimaldi , Andrea Ghiglietti , Leen Hatem , Hosam Mahmoud

A basic experiment in probability theory is drawing without replacement from an urn filled with multiple balls of different colours. Clearly, it is physically impossible to overdraw, that is, to draw more balls from the urn than it…

Probability · Mathematics 2023-12-21 Bart Jacobs , Dario Stein

This paper studies a very general urn model stimulated by designs in clinical trials, where the number of balls of different types added to the urn at trial n depends on a random outcome directed by the composition at trials 1,2,...,n-1.…

Probability · Mathematics 2007-05-23 Zhi-Dong Bai , Feifang Hu

We consider a special case of the generalized P\'{o}lya's urn model introduced by Benaim et al (2013). Given a finite connected graph $G$, place a bin at each vertex. Two bins are called a pair if they share an edge of $G$. At discrete…

Probability · Mathematics 2014-10-06 Jun Chen , Cyrille Lucas

We consider an urn model, whose replacement matrix has all entries nonnegative and is balanced, that is, has constant row sums. We obtain the rates of the counts of balls corresponding to each color for the strong laws to hold. The analysis…

Probability · Mathematics 2017-09-05 Amites Dasgupta , Krishanu Maulik

In the face of adverse motives, it is indispensable to achieve a consensus. Elections have been the canonical way by which modern democracy has operated since the 17th century. Nowadays, they regulate markets, provide an engine for modern…

Machine Learning · Computer Science 2026-01-06 Hao Xiang Li , Yash Shah , Lorenzo Giusti

Urn models play an important role to express various basic ideas in probability theory. Here we extend this urn model with tubes. An urn contains coloured balls, which can be drawn with probabilities proportional to the numbers of balls of…

Probability · Mathematics 2024-08-07 Bart Jacobs

This article describes a purely analytic approach to urn models of the generalized or extended P\'olya-Eggenberger type, in the case of two types of balls and constant ``balance,'' that is, constant row sum. The treatment starts from a…

Probability · Mathematics 2007-05-23 Philippe Flajolet , Joaquim Gabarro , Helmut Pekari

In this paper, we consider a multi-drawing urn model with random addition. At each discrete time step, we draw a sample of m balls. According to the composition of the drawn colors, we return the balls together with a random number of balls…

Probability · Mathematics 2018-02-14 Rafik Aguech , Nabil Lasmar , Olfa Selmi

We collect, survey and develop methods of (one-dimensional) stochastic approximation in a framework that seems suitable to handle fairly broad generalizations of Polya urns. To show the applicability of the results we determine the limiting…

Probability · Mathematics 2010-02-22 Henrik Renlund