Exploiting experts' knowledge can significantly increase the quality of Bayesian network (BN) structures produced by learning algorithms. However, in practice, experts may not be 100% confident about opinions they provide. Worst, latter also conflicting. Including such specific algorithms is therefore complex. In literature, there exist a few score-based that exploit both data and existence/abs...

We study the design of contracts that incentivize experts to collect information and truthfully report it a decision maker. depart from most previous literature by assuming transfers cannot depend on realized state or ex post payoff The contract thus has induce “monitor each other” making contingent entire vector reports. characterize least costly implements any given efforts derive cost functi...

We consider a cross-calibration test of predictions by multiple potential experts in a stochastic environment. This test checks whether each expert is calibrated conditional on the predictions made by other experts. We show that this test is good in the sense that a true expert—one informed of the true distribution of the process—is guaranteed to pass the test no matter what the other potential...