no code implementations • 2 Apr 2020 • Aritra Mitra, John A. Richards, Saurabh Bagchi, Shreyas Sundaram
We prove that our rule guarantees convergence to the true state exponentially fast almost surely despite sparse communication, and that it has the potential to significantly reduce information flow from uninformative agents to informative agents.
no code implementations • 4 Sep 2019 • Aritra Mitra, John A. Richards, Shreyas Sundaram
We introduce a simple time-triggered protocol to achieve communication-efficient non-Bayesian learning over a network.
no code implementations • 5 Jul 2019 • Aritra Mitra, John A. Richards, Shreyas Sundaram
We study a setting where a group of agents, each receiving partially informative private signals, seek to collaboratively learn the true underlying state of the world (from a finite set of hypotheses) that generates their joint observation profiles.
no code implementations • 14 Mar 2019 • Aritra Mitra, John A. Richards, Shreyas Sundaram
Under minimal requirements on the signal structures of the agents and the underlying communication graph, we establish consistency of the proposed belief update rule, i. e., we show that the actual beliefs of the agents asymptotically concentrate on the true state almost surely.