具有个体和集体强化的相互作用随机系统的同步和波动

IF 0.5 4区 数学 Q4 STATISTICS & PROBABILITY Stochastic Models Pub Date : 2023-10-17 DOI:10.1080/15326349.2023.2267663
Pierre-Yves Louis, Meghdad Mirebrahimi
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引用次数: 3

摘要

摘要Pólya是强化随机过程最具代表性的例子。它导致一个随机的(非退化的)时间限制。弗里德曼骨灰盒是一种自然的概括,其几乎确定的时间限制不再是随机的。在这项工作中,在之前最近的工作流中,我们引入了一组新的(有限大小)强化随机过程系统,通过平均场类型的额外集体强化相互作用。两种强化规则强度(一个组件,一个集合)通过(可能)两种不同的速率进行调整。在特殊情况下,这些强化是Pólya或弗里德曼类型的,因此可能导致限制,可能是随机的,也可能不是。需要考虑不同的参数体系。我们陈述两种结果。首先,我们研究了时间渐近性,证明了L2和a.s.收敛性总是成立的。此外,所有组件共享相同的时间限制(所谓的同步现象)。我们根据所考虑的参数范围研究了极限(随机/确定性)的性质。其次,我们通过证明中心极限定理来研究波动。比例系数根据所考虑的制度而变化。这让我们对许多不同的收敛速度有了深入的了解。特别是,我们确定了同步比向共享时间限制收敛更快的制度。关键词:几乎肯定收敛中心极限定理波动相互作用随机系统强化随机过程稳定收敛同步2010数学学科分类:初级60k35初级60f1560f05次级62l20次级62P35致谢我要感谢Pierre-Yves Louis教授向我介绍这个问题以及所有有用的评论和讨论。我也非常感谢裁判非常有建设性的反馈。披露声明作者未报告潜在的利益冲突。
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Synchronization and fluctuations for interacting stochastic systems with individual and collective reinforcement
AbstractThe Pólya urn is the most representative example of a reinforced stochastic process. It leads to a random (non degenerated) time-limit. The Friedman urn is a natural generalization whose almost sure (a.s.) time-limit is not random any more. In this work, in the stream of previous recent works, we introduce a new family of (finite size) systems of reinforced stochastic processes, interacting through an additional collective reinforcement of mean field type. The two reinforcement rules strengths (one component-wise, one collective) are tuned through (possibly) two different rates. In special cases, these reinforcements are of Pólya or Friedman type as in urn contexts and may thus lead to limits which may be random or not. Different parameter regimes need to be considered. We state two kind of results. First, we study the time-asymptotic and show that L2 and a.s. convergence always holds. Moreover, all the components share the same time-limit (so called synchronization phenomenon). We study the nature of the limit (random/deterministic) according to the parameters’ regime considered. Second, we study fluctuations by proving central limit theorems. Scaling coefficients vary according to the regime considered. This gives insights into many different rates of convergence. In particular, we identify the regimes where synchronization is faster than convergence toward the shared time-limit.Keywords: Almost sure convergencecentral limit theoremsfluctuationsinteracting random systemsreinforced stochastic processesstable convergencesynchronization2010 Mathematics Subject Classification: Primary 60K35Primary 60F1560F05Secondary 62L20Secondary 62P35 AcknowledgmentsI would like to thank Professor Pierre-Yves Louis for introducing me to the problem and for all the useful comments and discussions. I am also very grateful for extremely constructive feedback from the referee.Disclosure statementNo potential conflict of interest was reported by the author(s).
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来源期刊
Stochastic Models
Stochastic Models 数学-统计学与概率论
CiteScore
1.30
自引率
14.30%
发文量
42
审稿时长
>12 weeks
期刊介绍: Stochastic Models publishes papers discussing the theory and applications of probability as they arise in the modeling of phenomena in the natural sciences, social sciences and technology. It presents novel contributions to mathematical theory, using structural, analytical, algorithmic or experimental approaches. In an interdisciplinary context, it discusses practical applications of stochastic models to diverse areas such as biology, computer science, telecommunications modeling, inventories and dams, reliability, storage, queueing theory, mathematical finance and operations research.
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