Optimal Information Discovery in Correlated Environments: Measuring the Value of Information
We study linear combinatorial optimization problems where uncertain disruptions may affect the components (i.e., coefficients) of the objective function. To mitigate the impact of these disruptions, a planner can allocate a limited probing budget to fully reveal the status of selected components, while unprobed components status must be estimated. In contrast to settings assuming independence, … Read more