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Consider an election where N seats are distributed among parties with proportions p_1,...,p_m of the votes. We study, for the common divisor and quota methods, the asymptotic distribution, and in particular the mean, of the seat excess of a…

Probability · Mathematics 2011-10-31 Svante Janson

This is a research endeavor in two parts. We study a class of balanced urn schemes on balls of two colours (say white and black). At each drawing, a sample of size $m\ge 1$ is drawn from the urn, and ball addition rules are applied. We…

Probability · Mathematics 2015-04-01 Markus Kuba , Hosam M. Mahmoud

This paper considers the $(n,k)$-Bernoulli--Laplace model in the case when there are two urns, the total number of red and white balls is the same, and the number of selections $k$ at each step is on the same asymptotic order as the number…

Online reinforcement learning agents are currently able to process an increasing amount of data by converting it into a higher order value functions. This expansion of the information collected from the environment increases the agent's…

Machine Learning · Computer Science 2021-02-04 Mirza Ramicic , Andrea Bonarini

We introduce a multi-colour multi-urn generalisation of the Bernoulli-Laplace urn model, consisting of $d$ urns, $m$ colours, and $dmn$ balls, with $dn$ balls of each colour and $mn$ balls in each urn. At each step, one ball is drawn…

Probability · Mathematics 2025-11-14 Ritesh Goenka , Jonathan Hermon , Dominik Schmid

We introduce a two-player model of reinforcement learning with memory. Past actions of an iterated game are stored in a memory and used to determine player's next action. To examine the behaviour of the model some approximate methods are…

Statistical Mechanics · Physics 2009-11-13 Adam Lipowski , Krzysztof Gontarek , Marcel Ausloos

Many networks do not live in isolation but are strongly interacting, with profound consequences on their dynamics. Here, we consider the case of two interacting social networks and, in the context of a simple model, we address the case of…

Physics and Society · Physics 2015-06-11 Arda Halu , Kun Zhao , Andrea Baronchelli , Ginestra Bianconi

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

Suppose you and your friend both do $n$ tosses of an unfair coin with probability of heads equal to $\alpha$. What is the behavior of the probability that you obtain at least $d$ more heads than your friend if you make $r$ additional…

Probability · Mathematics 2012-03-19 Wenbo V. Li , Vladislav V. Vysotsky

We consider a two-round election model involving $m$ voters and $n$ candidates. Each voter is endowed with a strict preference list ranking the candidates. In the first round, the candidates are partitioned into two subsets, $A$ and $B$,…

Computer Science and Game Theory · Computer Science 2026-03-17 Emilio De Santis , Antonio Di Crescenzo , Verdiana Mustaro

A P\'olya urn process is a Markov chain that models the evolution of an urn containing some coloured balls, the set of possible colours being $\{1,\ldots,d\}$ for $d\in \mathbb{N}$. At each time step, a random ball is chosen uniformly in…

Probability · Mathematics 2017-03-13 Cécile Mailler , Jean-François Marckert

Consider an urn initially containing $b$ black and $w$ white balls. Select a ball at random and observe its color. If it is black, stop. Otherwise, return the white ball together with another white ball to the urn. Continue selecting at…

Probability · Mathematics 2019-11-05 Norbert Henze , Mark P. Holmes

We establish a link between multiwinner elections and apportionment problems by showing how approval-based multiwinner election rules can be interpreted as methods of apportionment. We consider several multiwinner rules and observe that…

Computer Science and Game Theory · Computer Science 2021-04-21 Markus Brill , Jean-François Laslier , Piotr Skowron

We study the joint asymptotics of forward and backward processes of numbers of non-empty urns in an infinite urn scheme. The probabilities of balls hitting the urns are assumed to satisfy the conditions of regular decrease. We prove weak…

Probability · Mathematics 2022-11-10 Mikhail Chebunin , Artyom Kovalevskii

The dynamics of interacting perceptrons is solved analytically. For a directed flow of information the system runs into a state which has a higher symmetry than the topology of the model. A symmetry breaking phase transition is found with…

Disordered Systems and Neural Networks · Physics 2007-05-23 W. Kinzel , R. Metzler , I. Kanter

Reinforcement learning methods have recently been very successful at performing complex sequential tasks like playing Atari games, Go and Poker. These algorithms have outperformed humans in several tasks by learning from scratch, using only…

Machine Learning · Computer Science 2021-09-28 Ajay Subramanian , Sharad Chitlangia , Veeky Baths

Consider an urn filled with balls, each labeled with one of several possible collective decisions. Now, let a random voter draw two balls from the urn and pick her more preferred as the collective decision. Relabel the losing ball with the…

Theoretical Economics · Economics 2024-03-28 Florian Brandl , Felix Brandt

We consider triangular P\'olya urns and show under very weak conditions a general strong limit theorem of the form $X_{ni}/a_{ni}\to \mathcal{X}_i$ a.s., where $X_{ni}$ is the number of balls of colour $i$ after $n$ draws; the constants…

Probability · Mathematics 2024-03-22 Svante Janson

We study a general preferential attachment and Polya's urn model. At each step a new vertex is introduced, which can be connected to at most one existing vertex. If it is disconnected, it becomes a pioneer vertex. Given that it is not…

Probability · Mathematics 2013-03-18 Andrea Collevecchio , Codina Cotar , Marco LiCalzi

We present the first reinforcement-learning model to self-improve its reward-modulated training implemented through a continuously improving "intuition" neural network. An agent was trained how to play the arcade video game Pong with two…

Artificial Intelligence · Computer Science 2016-09-26 Matt Oberdorfer , Matt Abuzalaf
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