Asymptotic properties of distributed social sampling algorithm
Liu, Qian1,2; He, Xingkang3; Fang, Haitao1,2
AbstractSocial sampling is a novel randomized message passing protocol inspired by social communication for opinion formation in social networks. In a typical social sampling algorithm, each agent holds a sample from the empirical distribution of social opinions at initial time, and it collaborates with other agents in a distributed manner to estimate the initial empirical distribution by randomly sampling a message from current distribution estimate. In this paper, we focus on analyzing the theoretical properties of the distributed social sampling algorithm over random networks. First, we provide a framework based on stochastic approximation to study the asymptotic properties of the algorithm. Then, under mild conditions, we prove that the estimates of all agents converge to a common random distribution, which is composed of the initial empirical distribution and the accumulation of quantized error. Besides, by tuning algorithm parameters, we prove the strong consistency, namely, the distribution estimates of agents almost surely converge to the initial empirical distribution. Furthermore, the asymptotic normality of estimation error generated by distributed social sample algorithm is addressed. Finally, we provide a numerical simulation to validate the theoretical results of this paper.
Keywordsocial networks opinion formation social sampling stochastic approximation random networks asymptotic normality
Indexed BySCI
Funding ProjectNational Key Research and Development Program of China[2016YFB0901900] ; National Natural Science Foundation of China[61573345]
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic
WOS IDWOS:000517247500001
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Document Type期刊论文
Corresponding AuthorHe, Xingkang
Affiliation1.Chinese Acad Sci, Acad Math & Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China
3.KTH Royal Inst Technol, Sch Elect Engn & Comp Sci, ACCESS Linnaeus Ctr, SE-10044 Stockholm, Sweden
Recommended Citation
GB/T 7714
Liu, Qian,He, Xingkang,Fang, Haitao. Asymptotic properties of distributed social sampling algorithm[J]. SCIENCE CHINA-INFORMATION SCIENCES,2020,63(1):15.
APA Liu, Qian,He, Xingkang,&Fang, Haitao.(2020).Asymptotic properties of distributed social sampling algorithm.SCIENCE CHINA-INFORMATION SCIENCES,63(1),15.
MLA Liu, Qian,et al."Asymptotic properties of distributed social sampling algorithm".SCIENCE CHINA-INFORMATION SCIENCES 63.1(2020):15.
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