.png){kind=icon}
返回
Distributed Social Learning With Imperfect Information
.png){kind=icon}
PRE
AI
DOI：10.1109/TNSE.2020.3010833.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We consider the social learning problem in the paper, where the individuals in a social group need to choose one of the given options with unknown stochastic qualities to gain payoffs. This problem has been attracting increasing attention in recent years, but most of the existing proposals entail perfect information to ensure the learning efficacy, while collecting information globally to support highly efficient learning entails considerable overhead in general social networks. In this paper, we propose an iterative three-staged algorithm consisting of sampling, selection and adoption in each iteration. In particular, in a general multi-hop social network (possibly with malicious nodes), we innovate in fully exploiting the imperfect information over the social network to achieve a nearly optimal regret with light-weight communication and time complexities. We also perform solid theoretic analysis and extensive simulations to verify the efficacy of our proposed algorithm.
Keyword:
Social network services
Bayes methods
Nickel
Spread spectrum communication
Heuristic algorithms
Random variables
Social groups
Social learning
imperfect information
random walk
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
I
IF:
7.9
论文数:
2.6K
被引数:
10.0K
机构
引用论文
Earthworms as an Ecological Indicator of Soil Recovery after Mechanized Logging Operations in Mixed Beech Forests.png)
Forests
OAAI
ForestsIF0
OAAI分享收藏
查看更多内容