Information acquisition and sequential belief refinement
Tara Javidi · 2016
Information acquisition and utilization problems (IAUP) form a class of stochastic decision problems in which a decision maker is faced with utilizing a stochastically varying (and uncontrollable) environment. However, the state of the environment, due to the limited nature of the measurements in terms of dimension/cost/accuracy, is only partially known to the decision maker. The decision maker, by carefully controlling the sequence of actions with uncertain outcomes and noisy measurements, dynamically refines the belief about the stochastically varying parameters of interest. A generalization of hidden Markov models and a special case of partially observable Markov models, information acquisition is both an informational problem as well as a control one.