Abstract
Some recent concepts and results on asymptotically optimal control rules in several classical stochastic adaptive control problems are reviewed and discussed. In particular, ways to resolve the apparent dilemma between the need for information and the objective of efficient control in these problems are presented. Asymptotic lower bounds on the minimal amount of information needed and a general heuristic principle are also given.

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