**Sequential Allocation with Minimal Switching**

Janis Hardwick

Statistics Department, University of Michigan

Quentin F. Stout

EECS Department, University of Michigan

The algorithms are quite general, and give users flexibility in incorporating practical considerations in the design of experiments. To show the usability of these algorithms, they are applied to a bandit problem and an estimation problem. It is observed that the expected number of switches grows approximately as the square root of the sample size, for sample sizes up to a few hundred. It is also observed that one can dramatically reduce the number of switches without substantially affecting the expected value of the objective function. Thus one need sacrifice only a small amount of statistical objective in order to achieve significant gains in practicality.

**Keywords:** adaptive sampling, switching costs, constraints,
bandit, estimation, dynamic programming, optimal tradeoffs

Copyright © 1996, 1997. | Last modified: 5 Mar 1997 |