Effects of asynchronism on evolutionary games

Grilo, Carlos; Correia, Luís

doi:10.1016/j.jtbi.2010.10.022

Cited by 25 publications

(23 citation statements)

References 48 publications

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“…Examples of such phenomena include periodic patterns in the Game of Life [4,12], several Elementary CA [13] and even the spatially-extended Prisoner's Dilemma [14]. From those examples, one may wonder that such observations can be only made in systems with an ad hoc deterministic transition rule, or whether it can also occur for models of natural phenomena, such as LGCA.…”

Section: Synchronous Singularitiesmentioning

confidence: 99%

First steps on asynchronous lattice-gas models with an application to a swarming rule

2013

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Lattice-gas cellular automata are often considered as a particular case of cellular automata in which additional constraints apply, such as conservation of particles or spatial exclusion. But what about their updating? How to deal with non-perfect synchrony? Novel definitions of asynchronism are proposed that respect the specific hypotheses of lattice-gas models. These definitions are then applied to a swarming rule in order to explore the robustness of the global emergent behaviour. In particular, we compare the synchronous and asynchronous case, and remark that antialignment of particles is no longer observed when a small critical amount of asynchronism is added.

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Section: Synchronous Singularitiesmentioning

confidence: 99%

First steps on asynchronous lattice-gas models with an application to a swarming rule

2013

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“…Due to the effects of assortment, the parameters for the infinite and well-mixed population of Section 2 cannot The fact that there is no inter-class learning favours selfish behaviour by allowing it to exploit altruistic individuals without causing those individuals to become selfish as well. This diminishes the opportunity for positive assortment by breaking up the cluster structure that benefits cooperation and punishment in the spatial model [50,51].…”

Section: Spatial Model: Resultsmentioning

confidence: 99%

Evolution of altruistic punishment in heterogeneous populations

Weerd

Verbrugge

2011

Journal of Theoretical Biology

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Evolutionary models for altruistic behaviour typically make the assumption of homogeneity: each individual has the same costs and benefits associated with cooperating with each other and punishing for selfish behaviour. In this paper, we relax this assumption by separating the population into heterogeneous classes, such that individuals from different classes differ in their ability to punish for selfishness. We compare the effects of introducing heterogeneity this way across two population models, that each represents a different type of population: the infinite and well-mixed population describes the way workers of social insects such as ants are organized, while a spatially structured population is more related to the way social norms evolve and are maintained in a social network.We find that heterogeneity in the effectiveness of punishment by itself has little to no effect on whether or not altruistic behaviour will stabilize in a population. In contrast, heterogeneity in the cost that individuals pay to punish for selfish behaviour allows altruistic behaviour to be maintained more easily. Fewer punishers are needed to deter selfish behaviour, and the individuals that punish will mostly belong to the class that pays a lower cost to do so. This effect is amplified when individuals that pay a lower cost for punishing inflict a higher punishment.The two population models differ when individuals that pay a low cost for punishing also inflict a lower punishment. In this situation, altruistic behaviour becomes harder to maintain in an infinite and well-mixed population. However, this effect does not occur when the population is spatially structured.

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“…Porém, alguns trabalhos sugerem que, dependendo do contexto, uma atualização assíncrona pode ser mais realista [4,6,9]. Nesse caso, há células que têm seus estados atualizados em instantes diferentes.…”

Section: Introductionunclassified

Um Modelo Epidemiológico Baseado em Autômatos Celulares Probabilistas Assíncronos

Chaves¹,

Oliveira²,

Monteiro³

2016

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics

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Resumo. Aqui, propõe-se um modelo epidemiológico baseado em autômato celular probabilista assíncrono, no qual os estados de uma fração μ das células são atualizados somente a cada β>1 passos de tempo. Mostra-se que os valores de μ e β influenciam o transiente, mas não afetam o regime permanente da dinâmica desse sistema.Palavras-chave. Autômato celular, assincronia, dinâmica populacional, epidemiologia, sistemas dinâmicos. IntroduçãoEpidemiologia teórica consiste no uso de modelos matemáticos no estudo da propagação de patógenos, visando prever a evolução temporal do número de indivíduos infectados, o que é crucial para a elaboração de medidas de controle [1]. No início do século XX, Kermack e McKendrik [8] propuseram um modelo epidemiológico conhecido pela sigla SIR. Descrito por equações diferenciais ordinárias, esse famoso modelo divide a população em três grupos de indivíduos: os suscetíveis, que são os que podem contrair a doença via contatos sociais; os infectados, que podem contaminar os suscetíveis; e os removidos, que são aqueles que tiveram a doença e ou se curaram e ficaram imunes, ou morreram. A sigla SIR decorre das iniciais desses três grupos.

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Effects of asynchronism on evolutionary games

Cited by 25 publications

References 48 publications

First steps on asynchronous lattice-gas models with an application to a swarming rule

First steps on asynchronous lattice-gas models with an application to a swarming rule

Evolution of altruistic punishment in heterogeneous populations

Um Modelo Epidemiológico Baseado em Autômatos Celulares Probabilistas Assíncronos

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