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Opinion dynamics and its understanding in social networks is an emerging field of research in recent years. Existing work mainly considers direct exchanges of opinions among agents under certain conditions. This paper addresses a problem where the agents of a network make and exchange decisions repeatedly in a multi-hypothesis scenario and learn from the neighbors' decisions. Two models are proposed...
In this article, we study social networks of agents, where agents learn not only from private signals (i.e., signals only available to the agents receiving them), but from other agents too. Based on all the available information, agents modify their beliefs in events of interest and make decisions on which actions to take based on the beliefs. In doing so, they optimize functions that reflect some...
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