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Learning-based Optimal Admission Control in a Single Server Queuing System
We show that the algorithm achieves an $O(1)$ regret when all optimal thresholds with full information are non-zero, and achieves an $O(\ln^{1+\epsilon}(N))$ regret for any specified $\epsilon>0$, in the case that an optimal threshold with full information is $0$ (i. e., an optimal policy is to reject all arrivals), where $N$ is the number of arrivals.
Order of Commitments in Bayesian Persuasion with Partial-informed Senders
Persuasion games with multiple senders have largely studied simultaneous commitment and signalling settings.
Bayesian Persuasion in Sequential Trials
The non-determined experiments (signals) in the multi-phase trial are to be chosen by the sender in order to persuade the receiver best.
