@inproceedings{44b90a06c1a5407888b6aa69b3b2d7b9,
title = "Bayesian social learning in linear networks of agents with random behavior",
abstract = "In this paper, we consider the problem of social learning in a network of agents where the agents make decisions onK hypotheses sequentially and broadcast their decisions to others. Each agent in the system has a private observation that is generated by one of the hypotheses. All the observations are independently generated from the same hypothesis. We study a setting where the agents randomly choose to make decisions prudently or non-prudently. A prudent decision is based on the private observation of the agent and all the previous decisions, whereas a non-prudent decision relies only on the private observation of the agent. We present a Bayesian learning method for the agents that exploits the information from other decisions. We analyze the asymptotical property of this system. A proof is presented that with the proposed decision policy, the posterior probability of the true hypothesis converges to one in probability. Simulation results are also provided.",
keywords = "Bayesian learning, non-prudent agents, prudent agents, random behavior, social learning",
author = "Yunlong Wang and Djuri{\'c}, {Petar M.}",
year = "2015",
month = aug,
day = "4",
doi = "10.1109/ICASSP.2015.7178598",
language = "English (US)",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3382--3386",
booktitle = "2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings",
note = "40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 ; Conference date: 19-04-2014 Through 24-04-2014",
}