On a Class of Random Walks with Reinforced Memory

被引:0
作者
Erich Baur
机构
[1] Bern University of Applied Sciences,
来源
Journal of Statistical Physics | 2020年 / 181卷
关键词
Reinforced random walks; Preferential attachment; Memory; Stable processes; Branching processes; Pólya urns; 60G50; 60G52; 60K35; 05C85;
D O I
暂无
中图分类号
学科分类号
摘要
This paper deals with different models of random walks with a reinforced memory of preferential attachment type. We consider extensions of the Elephant Random Walk introduced by Schütz and Trimper (Phys Rev E 70:044510(R), 2004) with stronger reinforcement mechanisms, where, roughly speaking, a step from the past is remembered proportional to some weight and then repeated with probability p. With probability 1-p\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1-p$$\end{document}, the random walk performs a step independent of the past. The weight of the remembered step is increased by an additive factor b≥0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$b\ge 0$$\end{document}, making it likelier to repeat the step again in the future. A combination of techniques from the theory of urns, branching processes and α\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha $$\end{document}-stable processes enables us to discuss the limit behavior of reinforced versions of both the Elephant Random Walk and its α\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha $$\end{document}-stable counterpart, the so-called Shark Random Swim introduced by Businger (J Stat Phys 172(3):701–717, 2004). We establish phase transitions, separating subcritical from supercritical regimes.
引用
收藏
页码:772 / 802
页数:30
相关论文
共 44 条
[1]  
Barabási A-L(1999)Emergence of scaling in random networks Science 286 509-512
[2]  
Albert R(2016)Elephant random walks and their connection to Pólya-type urns Phys. Rev. E 49 052134-1163
[3]  
Baur E(2017)A martingale approach for the elephant random walk J. Phys. A 51 015201-103
[4]  
Bertoin J(2019)On the multi-dimensional elephant random walk J. Stat. Phys. 175 1146-717
[5]  
Bercu B(2019)A version of Herbert A. Simon’s model with slowly fading memory and its connections to branching processes J. Stat. Phys. 176 679-2706
[6]  
Bercu B(2015)Supercritical percolation on large scale-free random trees Ann. Appl. Probab. 25–1 81-1292
[7]  
Laulin L(2018)The shark random swim (Lévy flight with memory) J. Stat. Phys. 172 701-245
[8]  
Bertoin J(2017)Central limit theorem for the elephant random walk J. Math. Phys. 58 053003-77
[9]  
Bertoin J(2017)A strong invariance principle for the elephant random walk J. Stat. Mech. Theory Exp. 12 123207-79
[10]  
Uribe Bravo G(2017)Edge- and vertex-reinforced random walks with super-linear reinforcement on infinite graphs Ann. Probab. 45 2655-2378