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Sequential Optimization Under Uncertainty

  • Tze Leung Lai
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 46)

Abstract

Herein we review certain problems in sequential optimization when the underlying dynamical system is not fully specified but has to be learned during the operation of the system. A prototypical example is the multi-armed bandit problem, which was one of Yakowitz’s many research areas. Other problems under review include stochastic approximation and adaptive control of Markov chains.

Keywords

Adaptive Control Switching Cost Stochastic Approximation Control Rule Bandit Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science + Business Media, Inc. 2002

Authors and Affiliations

  • Tze Leung Lai
    • 1
  1. 1.Stanford UniversityUSA

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