Randomization and Simplification
AbstractRandomization may add beneficial flexibility to the construction of optimal simple decision rules in dynamic environments. A decision maker, restricted to the use of simple rules, may find a stochastic rule that strictly outperforms all deterministic ones. This is true even in highly separable Markovian environments where the set of feasible choices is stationary and the decision maker's choices have no influence on future payoff functions. In separable environments, however, the period selection of an action can still be deterministic; only the transitions in the evolution of his behavior may require randomization.
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Bibliographic InfoPaper provided by Northwestern University, Center for Mathematical Studies in Economics and Management Science in its series Discussion Papers with number 1283.
Date of creation: Jan 2000
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- NEP-ALL-2000-10-05 (All new papers)
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