Non-Bayesian social learning with observation reuse and soft switching

Non-Bayesian social learning with observation reuse and soft switching

We propose a non-Bayesian social learning update rule for agents in a network, which minimizes the sum of the Kullback-Leibler divergence between the true distribution generating the agents’ local observations and the agents’ beliefs (parameterized by a hypothesis set), and a weighted varentropy-rel...

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書目詳細資料
Main Authors:	Md. Zulfiquar Ali Bhotto, Tay, Wee Peng
其他作者:	School of Electrical and Electronic Engineering
格式:	Article
語言:	English
出版:	2019
主題:	DRNTU::Engineering::Electrical and electronic engineering Non-Bayesian Social Learning Misinforming Agent
在線閱讀:	https://hdl.handle.net/10356/102641 http://hdl.handle.net/10220/48151
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Nanyang Technological University
語言:	English

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