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Introduction

  • S. BhatnagarEmail author
  • H. Prasad
  • L. Prashanth
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 434)

Abstract

Optimization methods play a central role in many engineering disciplines. In this chapter, we give a broad overview of the optimization settings and algorithms including simultaneous perturbation approaches as well as give a brief summary of later chapters.

Keywords

Reinforcement Learning Queue Length Markov Decision Process Stochastic Optimization Stochastic Approximation 
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-Verlag London 2013

Authors and Affiliations

  1. 1.Department of Computer Science and AutomationIndian Institute of ScienceBangaloreIndia

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