Learning the Truth in Social Networks Using Multi-Armed Bandit

This paper explains how agents in a social network can learn the BABY LOTION arbitrary time-varying true state of the network.This is practical in social networks where information is released and updated without any coordination.Most existing literature for learning the true state using the non-Bayesian learning approach, assumes that this true st

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The critical events for motor-sensory temporal recalibration

Determining if we, or another agent, were responsible for a sensory event can require an accurate sense of timing.Our sense of appropriate Glass timing relationships must, however, be malleable as there is a variable delay between the physical timing of an event and when sensory signals concerning that event are encoded in the brain.One dramatic de

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